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  },
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  },
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  },
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  },
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   "source": "https://github.com/vihari/crossgrad",
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    "Cross-Gradient Adversarial Data Augmentation"
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  },
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  },
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    "DexGraspNet dataset"
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  },
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    "COCO Dataset",
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    "Open3D",
    "Open3D Library",
    "isl-org/Open3D",
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    "dji-sdk/Payload-SDK"
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    "人工智能系统影响评估"
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  },
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    "IBM AI Security Baseline"
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  },
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    "fortiss/OntoGSN"
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    "26262",
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    "8800",
    "Road vehicles Safety and AI"
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  },
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    "预期功能安全"
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  },
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    "dSPACE SCALEXIO"
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    "libact",
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    "MTSAC MTPPO MAML library"
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    "Bakshy 2014 field experiments"
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  },
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    "Batch-Constrained Q-learning official"
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   "aliases": [
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    "BEAR PyTorch",
    "Bootstrapping Error Accumulation Reduction official"
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    "rail-berkeley bear"
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   "source": "https://github.com/google-research/google-research/tree/master/behavior_regularized_offline_rl",
   "aliases": [
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    "behavior_regularized_offline_rl",
    "BRAC TF1 official"
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   "aliases": [
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    "rail-berkeley brac"
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   "aliases": [
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  },
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  },
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    "honeybadgerbft python",
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    "Differentiable Branched Discrete Elastic Rods"
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  },
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    "PyFleX Rope",
    "SoftGym Rope Manipulation"
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  },
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    "SoftAgent",
    "SoftGym RL baselines"
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  },
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   "source": "https://github.com/Dingry/BunnyVisionPro",
   "aliases": [
    "Bunny-VisionPro",
    "BunnyVisionPro"
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  },
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   "source": "https://github.com/stepjam/RLBench",
   "aliases": [
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  },
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    "UnityEngine.Cloth"
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  },
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  },
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  },
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  },
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  },
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   "name": "Intel RealSense D415 Depth Camera",
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   "source": "https://www.intelrealsense.com/depth-camera-d415/",
   "aliases": [
    "RealSense D415",
    "Intel D415"
   ]
  },
  "AST_007ac7f2": {
   "name": "VCD CoRL 2021 Paper",
   "type": "tool",
   "source": "https://arxiv.org/abs/2105.10389",
   "aliases": [
    "arxiv 2105.10389",
    "Visible Connectivity Dynamics Paper"
   ]
  },
  "AST_86ada95e": {
   "name": "大尺度移动布料铺展",
   "type": "framework",
   "source": "https://arxiv.org/abs/2308.10401",
   "aliases": [
    "Mobile Cloth Spreading Framework",
    "LSM Cloth Spreading"
   ]
  },
  "AST_9b39bfbc": {
   "name": "Chu et al. CASE 2023 Paper",
   "type": "tool",
   "source": "https://arxiv.org/abs/2308.10401",
   "aliases": [
    "arxiv 2308.10401",
    "Large-scale Mobile Cloth Spreading Paper"
   ]
  },
  "AST_e112f21d": {
   "name": "PyTorch3D",
   "type": "tool",
   "source": "https://github.com/facebookresearch/pytorch3d",
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  },
  "AST_1e7af632": {
   "name": "Taichi",
   "type": "framework",
   "source": "https://github.com/taichi-dev/taichi",
   "aliases": [
    "DiffTaichi"
   ]
  },
  "AST_5d452e55": {
   "name": "Cloth-Splatting",
   "type": "package",
   "source": "https://github.com/KTH-RPL/cloth-splatting",
   "aliases": []
  },
  "AST_bc129a79": {
   "name": "diff-gaussian-rasterization",
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   "source": "https://github.com/graphdeco-inria/diff-gaussian-rasterization",
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  },
  "AST_13dd9e7b": {
   "name": "3D Gaussian Splatting",
   "type": "framework",
   "source": "https://github.com/graphdeco-inria/gaussian-splatting",
   "aliases": [
    "3DGS",
    "gaussian-splatting"
   ]
  },
  "AST_99966f15": {
   "name": "UniClothDiff",
   "type": "package",
   "source": "https://github.com/Tongxuan259/UniClothDiff",
   "aliases": [
    "UniClothDiff"
   ]
  },
  "AST_ca78c09d": {
   "name": "HuggingFace Diffusers",
   "type": "framework",
   "source": "https://github.com/huggingface/diffusers",
   "aliases": [
    "diffusers"
   ]
  },
  "AST_1f9b3035": {
   "name": "synthetic-cloth-data",
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   "source": "https://github.com/tlpss/synthetic-cloth-data",
   "aliases": [
    "synthetic-cloth-data"
   ]
  },
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   "source": "https://github.com/tlpss/keypoint-detection",
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    "keypoint-detection"
   ]
  },
  "AST_bbbda417": {
   "name": "aRTF Clothes Dataset",
   "type": "dataset",
   "source": "https://github.com/tlpss/aRTF-Clothes-dataset",
   "aliases": [
    "aRTF-Clothes"
   ]
  },
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    "airo-blender"
   ]
  },
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   "name": "GarmentNets",
   "type": "package",
   "source": "https://github.com/real-stanford/garmentnets",
   "aliases": [
    "GarmentNets"
   ]
  },
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   "name": "libigl",
   "type": "tool",
   "source": "https://github.com/libigl/libigl",
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    "libigl"
   ]
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   "source": "https://github.com/nmwsharp/potpourri3d",
   "aliases": [
    "potpourri3d"
   ]
  },
  "AST_68da5aaa": {
   "name": "Kong Gateway",
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   "source": "https://github.com/Kong/kong",
   "aliases": [
    "Kong",
    "Kong Gateway",
    "Kong/kong"
   ]
  },
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   "name": "Open Policy Agent",
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   "source": "https://github.com/open-policy-agent/opa",
   "aliases": [
    "OPA",
    "open-policy-agent/opa"
   ]
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   "name": "Keycloak",
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   "source": "https://github.com/keycloak/keycloak",
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    "Keycloak IAM",
    "keycloak/keycloak"
   ]
  },
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    "jpadilla/pyjwt",
    "pyjwt"
   ]
  },
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    "mpdavis/python-jose"
   ]
  },
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   "source": "https://github.com/envoyproxy/ratelimit",
   "aliases": [
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    "envoyproxy/ratelimit"
   ]
  },
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   "name": "limits",
   "type": "package",
   "source": "https://github.com/alisaifee/limits",
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    "limits",
    "alisaifee/limits",
    "python-limits"
   ]
  },
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   "name": "redis-py",
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   "source": "https://github.com/redis/redis-py",
   "aliases": [
    "redis-py",
    "redis/redis-py",
    "redis"
   ]
  },
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   "source": "https://aws.amazon.com/api-gateway/",
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    "AWS API Gateway",
    "Amazon API Gateway"
   ]
  },
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    "Cloudflare WAF",
    "CF WAF"
   ]
  },
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   "name": "ModSecurity",
   "type": "framework",
   "source": "https://github.com/owasp-modsecurity/ModSecurity",
   "aliases": [
    "ModSecurity",
    "ModSecurity v3",
    "owasp-modsecurity/ModSecurity"
   ]
  },
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   "name": "OWASP Core Rule Set",
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    "OWASP CRS",
    "Core Rule Set",
    "coreruleset/coreruleset",
    "CRS"
   ]
  },
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   "aliases": [
    "jsonschema",
    "python-jsonschema/jsonschema",
    "python-jsonschema"
   ]
  },
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    "pydantic/pydantic",
    "pydantic V2"
   ]
  },
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    "tiangolo/fastapi"
   ]
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   "source": "https://aws.amazon.com/waf/",
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    "AWS WAF",
    "Amazon WAF"
   ]
  },
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   "source": "https://github.com/grafana/tempo",
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    "Tempo"
   ]
  },
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   "name": "Grafana Mimir",
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   "source": "https://github.com/grafana/mimir",
   "aliases": [
    "Mimir"
   ]
  },
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    "Hugging Face Hub"
   ]
  },
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   "source": "https://github.com/foxglove/mcap",
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    "MCAP Format"
   ]
  },
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    "Rerun"
   ]
  },
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   "aliases": [
    "ros2 bag",
    "rosbag2"
   ]
  },
  "AST_92052be2": {
   "name": "rosbags",
   "type": "tool",
   "source": "https://github.com/rosbags/rosbags",
   "aliases": [
    "rosbags python"
   ]
  },
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   "source": "https://github.com/kubeedge/kubeedge",
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    "kubeedge/kubeedge"
   ]
  },
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   "aliases": [
    "EdgeMesh",
    "kubeedge/edgemesh"
   ]
  },
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   "name": "OpenYurt",
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    "openyurtio/openyurt"
   ]
  },
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   "name": "Raven",
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   "aliases": [
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    "openyurtio/raven",
    "OpenYurt Raven"
   ]
  },
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    "FogROS2 framework",
    "BerkeleyAutomation/FogROS2",
    "fogros2"
   ]
  },
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   "source": "https://github.com/WireGuard/wireguard-tools",
   "aliases": [
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    "wireguard-tools",
    "wg"
   ]
  },
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   "type": "paper",
   "source": "https://12factor.net/",
   "aliases": []
  },
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   "type": "framework",
   "source": "https://github.com/kedacore/keda",
   "aliases": [
    "Kubernetes Event-Driven Autoscaling"
   ]
  },
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   "source": "https://12factor.net/concurrency",
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    "12-Factor App",
    "Twelve-Factor"
   ]
  },
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   "source": "https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/",
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    "K8s HPA design"
   ]
  },
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   "name": "Twelve-Factor App - Disposability",
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   "source": "https://12factor.net/disposability",
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  },
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   "name": "Alertmanager",
   "type": "framework",
   "source": "https://github.com/prometheus/alertmanager",
   "aliases": []
  },
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   "name": "node_exporter",
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   "source": "https://github.com/prometheus/node_exporter",
   "aliases": []
  },
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   "name": "Jaeger",
   "type": "tool",
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   "aliases": []
  },
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   "type": "tool",
   "source": "https://ieeexplore.ieee.org/document/7562668",
   "aliases": [
    "Mao 2016",
    "Dynamic Computation Offloading JSAC",
    "Lyapunov MEC Offloading Paper"
   ]
  },
  "AST_a61be2b1": {
   "name": "Mao 2017 MEC Survey",
   "type": "tool",
   "source": "https://doi.org/10.1109/COMST.2016.2636172",
   "aliases": [
    "Mao 2017 Survey",
    "MEC Communication Survey",
    "A Survey on Mobile Edge Computing"
   ]
  },
  "AST_1bc71721": {
   "name": "DROO",
   "type": "package",
   "source": "https://github.com/revenol/DROO",
   "aliases": [
    "DROO",
    "revenol/DROO",
    "Deep Reinforcement Offloading Code"
   ]
  },
  "AST_41ee5dac": {
   "name": "Huang 2020 TMC DROO",
   "type": "tool",
   "source": "https://ieeexplore.ieee.org/document/8771176",
   "aliases": [
    "Huang 2020 TMC",
    "DROO Paper",
    "Deep RL Online Offloading"
   ]
  },
  "AST_4c5628ae": {
   "name": "LyDROO",
   "type": "package",
   "source": "https://github.com/revenol/LyDROO",
   "aliases": [
    "revenol/LyDROO",
    "Lyapunov-guided DRL Offloading Code",
    "Bi 2021 TWC LyDROO",
    "Bi 2021 TWC",
    "LyDROO Paper",
    "Lyapunov-guided DRL Offloading"
   ]
  },
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   "name": "Chen 2015 TPDS Decentralized Offloading Game",
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   "source": "https://ieeexplore.ieee.org/document/6848397",
   "aliases": [
    "Chen 2015 TPDS",
    "Decentralized Offloading Game",
    "Potential Game Offloading Paper"
   ]
  },
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   "name": "AWS RoboMaker",
   "type": "simulator",
   "source": "https://docs.aws.amazon.com/robomaker/latest/dg/what-is-robomaker.html",
   "aliases": [
    "AWS RoboMaker Simulation",
    "RoboMaker SimulationJob",
    "AWS cloud robotics simulation"
   ]
  },
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   "name": "KubeRay",
   "type": "framework",
   "source": "https://github.com/ray-project/kuberay",
   "aliases": [
    "KubeRay operator",
    "ray-project/kuberay",
    "RayCluster CRD"
   ]
  },
  "AST_0003f921": {
   "name": "TEASER++",
   "type": "package",
   "source": "https://github.com/MIT-SPARK/TEASER-plusplus",
   "aliases": [
    "MIT SPARK TEASER",
    "TEASER",
    "TEASER++",
    "TEASER-plusplus",
    "TLS registration",
    "Truncated Least Squares Registration"
   ]
  },
  "AST_1a5ff3b7": {
   "name": "BILP-Q",
   "type": "tool",
   "source": "https://github.com/supreethmv/BILP-Q",
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  },
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   "name": "GCS-Q",
   "type": "tool",
   "source": "https://github.com/supreethmv/GCS-Q",
   "aliases": []
  },
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   "name": "QuACS",
   "type": "tool",
   "source": "https://github.com/supreethmv/QuACS",
   "aliases": []
  },
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   "name": "IEC 61508-7",
   "type": "tool",
   "source": "https://webstore.iec.ch/publication/6027",
   "aliases": [
    "IEC 61508 Part 7"
   ]
  },
  "AST_3d401026": {
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   "type": "tool",
   "source": "https://m.douban.com/book/subject/2123634/",
   "aliases": [
    "Storey SCCS"
   ]
  },
  "AST_7b9cd5c1": {
   "name": "Siemens Patent CN102713857A (Fail-Safe Hardware-Independent Floating-Point Operations)",
   "type": "tool",
   "source": "https://www.xjishu.com/zhuanli/55/201080011920.html/",
   "aliases": [
    "Siemens Patent CN102713857A"
   ]
  },
  "AST_2b0b425f": {
   "name": "IEC 61508-2:2010",
   "type": "tool",
   "source": "https://webstore.iec.ch/publication/5516",
   "aliases": [
    "IEC 61508 Part 2"
   ]
  },
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   "name": "EN 50128",
   "type": "tool",
   "source": "https://www.cencenelec.eu/",
   "aliases": [
    "EN 50128:2011"
   ]
  },
  "AST_46341ba1": {
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   "type": "tool",
   "source": "https://www.rtca.org/products/do-178c/",
   "aliases": [
    "DO-178C"
   ]
  },
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   "source": "https://github.com/DependableSystemsLab/LLTFI",
   "aliases": [
    "Low-Level Tensor Fault Injector"
   ]
  },
  "AST_9da90a04": {
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   "type": "framework",
   "source": "https://github.com/huggingface/smolagents",
   "aliases": [
    "HuggingFace smolagents",
    "smolagents CodeAgent",
    "smolagents"
   ]
  },
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   "name": "Anthropic 程序化工具调用",
   "type": "framework",
   "source": "https://docs.anthropic.com/en/docs/agents-and-tools/tool-use/programmatic-tool-calling",
   "aliases": [
    "Anthropic PTC",
    "code_execution_20260120",
    "Programmatic Tool Calling"
   ]
  },
  "AST_e332950d": {
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   "type": "framework",
   "source": "https://github.com/SonarSource/sonarqube",
   "aliases": [
    "SonarQube Server",
    "SonarCloud",
    "SonarSource",
    "sonarqube-scan-action"
   ]
  },
  "AST_4fb670ce": {
   "name": "Codecov",
   "type": "tool",
   "source": "https://github.com/codecov/codecov-action",
   "aliases": [
    "codecov-action",
    "codecov.io",
    "Codecov Bash Uploader"
   ]
  },
  "AST_e771ef33": {
   "name": "Cppcheck",
   "type": "tool",
   "source": "https://github.com/danmar/cppcheck",
   "aliases": [
    "cppcheck",
    "danmar/cppcheck"
   ]
  },
  "AST_6482c830": {
   "name": "clang-tidy",
   "type": "tool",
   "source": "https://clang.llvm.org/extra/clang-tidy/",
   "aliases": [
    "clang-tidy",
    "run-clang-tidy",
    "LLVM clang-tidy"
   ]
  },
  "AST_b829534c": {
   "name": "pre-commit",
   "type": "tool",
   "source": "https://github.com/pre-commit/pre-commit",
   "aliases": [
    "pre-commit",
    "pre-commit-hooks",
    ".pre-commit-config.yaml"
   ]
  },
  "AST_70b06fa9": {
   "name": "LDRA TBvision",
   "type": "tool",
   "source": "https://www.ldra.com/en/tbvision-automated-source-code-analysis",
   "aliases": [
    "LDRA",
    "TBvision",
    "LDRAcover",
    "LDRAunit"
   ]
  },
  "AST_b986ce7d": {
   "name": "Semgrep",
   "type": "tool",
   "source": "https://github.com/returntocorp/semgrep",
   "aliases": [
    "semgrep",
    "returntocorp/semgrep",
    "Semgrep CI"
   ]
  },
  "AST_52ad1c5d": {
   "name": "Gitleaks",
   "type": "tool",
   "source": "https://github.com/gitleaks/gitleaks",
   "aliases": [
    "gitleaks",
    "gitleaks/gitleaks",
    "Git secret scan"
   ]
  },
  "AST_65ed49e2": {
   "name": "EEGNet",
   "type": "model",
   "source": "https://github.com/vlawhern/arl-eegmodels",
   "aliases": [
    "arl-eegmodels"
   ]
  },
  "AST_438f5909": {
   "name": "Pupil Core",
   "type": "tool",
   "source": "https://github.com/pupil-labs/pupil",
   "aliases": [
    "pupil-labs"
   ]
  },
  "AST_614262d9": {
   "name": "SAT Model",
   "type": "framework",
   "source": "https://www.arl.army.mil/",
   "aliases": [
    "Situation Awareness-based Agent Transparency Model"
   ]
  },
  "AST_f69071f9": {
   "name": "TEPR 特征提取模块",
   "type": "package",
   "source": "https://github.com/scipy/scipy",
   "aliases": [
    "TEPR Extractor"
   ]
  },
  "AST_a774dc16": {
   "name": "OpenMATB",
   "type": "framework",
   "source": "https://github.com/juliencegarra/OpenMATB",
   "aliases": [
    "MATB-II Python",
    "OpenMATB Framework"
   ]
  },
  "AST_65e1c78e": {
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    "Boustrophedon Cellular Decomposition"
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    "force_mode_controller"
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  },
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   "aliases": [
    "mahao1001 Robot-polishing",
    "adaptive impedance polishing"
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  },
  "AST_ba22bbd4": {
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    "ur10e_force_control_comparison"
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  },
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   "source": "https://doi.org/10.1109/ACCESS.2020.3022930",
   "aliases": [
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    "Li 2020 IEEE Access"
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  },
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   "aliases": [
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    "Active End-Effector PMMA"
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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   "type": "model",
   "source": "https://www.cambridge.org/core/books/cognitive-structure-of-emotions/ [待核查]",
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    "Ortony Clore Collins Emotion Model"
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  },
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   "source": "https://link.springer.com/article/10.1007/s10458-009-9081-5 [待核查]",
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  },
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    "EEGS Emotion Model"
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  },
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   "source": "Gebhard, P. (2005). ALMA: A Layered Model of Affect. AAMAS 2005 Workshop. [待核查]",
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    "A Layered Model of Affect"
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  },
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    "Emotion in RL Agents Survey"
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  },
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    "Appraisal Guided PPO"
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  },
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    "Affect Driven Robot Personality"
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  },
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    "ALIZ-E Project"
   ]
  },
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    "User Satisfaction Estimation with Dialogue Act"
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  },
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   "source": "Amazon 内部（不公开）",
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    "Alexa User Satisfaction Data"
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  },
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   "source": "https://www.semanticscholar.org/author/Mohammad-Kachuee/2118356764",
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    "Self-Supervised Contrastive USE",
    "Amazon Alexa USE"
   ]
  },
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    "LLM OCC Zero Shot",
    "Fine-grained Affective Processing LLM"
   ]
  },
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   "source": "https://arxiv.org/abs/2405.20189",
   "aliases": [
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    "Nadine Social Robot"
   ]
  },
  "AST_e1823b2d": {
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   "source": "https://arxiv.org/abs/2402.11571",
   "aliases": [
    "Haru",
    "Haru LLM Robot"
   ]
  },
  "AST_b82d36fd": {
   "name": "PERCY ROS GPT-4 System",
   "type": "framework",
   "source": "https://arxiv.org/abs/2503.16473",
   "aliases": [
    "PERCY",
    "PERCY Personal Emotional Robot"
   ]
  },
  "AST_233bdf57": {
   "name": "EVOLVE LLM Emotion Visual Learning",
   "type": "framework",
   "source": "https://arxiv.org/abs/2412.20632",
   "aliases": [
    "EVOLVE",
    "Emotion Visual Output Learning"
   ]
  },
  "AST_8330c8d3": {
   "name": "SAFE Empathetic Cues LLM Framework",
   "type": "framework",
   "source": "https://arxiv.org/abs/2308.16529",
   "aliases": [
    "SAFE Framework",
    "Empathetic Cues LLM"
   ]
  },
  "AST_cf9c06a7": {
   "name": "AIOS",
   "type": "framework",
   "source": "https://github.com/agiresearch/AIOS",
   "aliases": []
  },
  "AST_d46a3825": {
   "name": "AIOS: LLM Agent Operating System",
   "type": "paper",
   "source": "https://arxiv.org/abs/2403.16971",
   "aliases": []
  },
  "AST_1d8a7dd4": {
   "name": "Architecting AgentOS: From Token-Level Context to Emergent System-Level Intelligence",
   "type": "paper",
   "source": "https://arxiv.org/abs/2602.20934",
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   "name": "OPPORTUNITY Activity Recognition",
   "type": "dataset",
   "source": "https://archive.ics.uci.edu/dataset/226",
   "aliases": [
    "Opportunity Dataset",
    "OPPORTUNITY Challenge",
    "UCI id=226"
   ]
  },
  "AST_4195b38f": {
   "name": "DeepConvLSTM",
   "type": "framework",
   "source": "https://github.com/sussexwearlab/DeepConvLSTM",
   "aliases": [
    "Deep Convolutional LSTM for HAR",
    "Ordonez-Roggen DeepConvLSTM"
   ]
  },
  "AST_c702923d": {
   "name": "HAR-stacked-residual-bidir-LSTMs",
   "type": "tool",
   "source": "https://github.com/guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs",
   "aliases": [
    "Deep Residual Bidir-LSTM for HAR",
    "HAR Residual Bidir LSTM"
   ]
  },
  "AST_6b2e5fbb": {
   "name": "CASAS Smart Home Datasets",
   "type": "dataset",
   "source": "https://casas.wsu.edu/datasets/",
   "aliases": [
    "CASAS",
    "WSU CASAS",
    "CASAS Smart Home"
   ]
  },
  "AST_5fb5159f": {
   "name": "van Kasteren House A/B/C",
   "type": "dataset",
   "source": "https://doi.org/10.2991/978-94-91216-05-3",
   "aliases": [
    "van Kasteren",
    "Kasteren ADL Dataset",
    "House A/B/C"
   ]
  },
  "AST_477932b8": {
   "name": "CASAS AL-Smarthome",
   "type": "tool",
   "source": "https://github.com/WSU-CASAS/AL-Smarthome",
   "aliases": [
    "AL-Smarthome",
    "CASAS Activity Learning",
    "WSU AL-Smarthome"
   ]
  },
  "AST_5c4ee0e4": {
   "name": "linuxptp",
   "type": "tool",
   "source": "https://github.com/richardcochran/linuxptp",
   "aliases": [
    "ptp4l",
    "phc2sys",
    "linuxptp",
    "linux PTP"
   ]
  },
  "AST_49eade39": {
   "name": "NVIDIA DriveWorks SDK",
   "type": "framework",
   "source": "https://developer.nvidia.com/drive/driveworks",
   "aliases": [
    "DriveWorks",
    "NVIDIA SAL",
    "DriveWorks SAL"
   ]
  },
  "AST_04e15d23": {
   "name": "Basler pylon SDK",
   "type": "tool",
   "source": "https://www.baslerweb.com/en/products/software/basler-pylon-camera-software-suite/",
   "aliases": [
    "pylon",
    "Basler pylon",
    "pylon Camera Software Suite"
   ]
  },
  "AST_a6d8df26": {
   "name": "HikRobot MVS SDK",
   "type": "tool",
   "source": "https://www.hikrobotics.com/en/machine-vision/machine-vision-software",
   "aliases": [
    "MVS",
    "HikRobot MVS",
    "海康 MVS",
    "Machine Vision Software"
   ]
  },
  "AST_58e50c4f": {
   "name": "GELLO Mechanical",
   "type": "framework",
   "source": "https://github.com/wuphilipp/gello_mechanical",
   "aliases": [
    "GELLO",
    "gello_mechanical",
    "3D printed leader arm"
   ]
  },
  "AST_3516f0e0": {
   "name": "ARX",
   "type": "tool",
   "source": "https://github.com/arx-deidentifier/arx",
   "aliases": [
    "ARX Data Anonymization Tool",
    "arx-deidentifier"
   ]
  },
  "AST_31a9d21b": {
   "name": "sdcMicro",
   "type": "tool",
   "source": "https://cran.r-project.org/package=sdcMicro",
   "aliases": [
    "sdcTools",
    "sdcMicro R package"
   ]
  },
  "AST_86c4b70b": {
   "name": "deface",
   "type": "tool",
   "source": "https://github.com/ORB-HD/deface",
   "aliases": [
    "deface video anonymizer",
    "ORB-HD deface"
   ]
  },
  "AST_edac2993": {
   "name": "CenterFace",
   "type": "model",
   "source": "https://github.com/Star-Clouds/centerface",
   "aliases": [
    "Star-Clouds CenterFace",
    "CenterNet face detector"
   ]
  },
  "AST_5fc2b96a": {
   "name": "Microsoft Presidio",
   "type": "tool",
   "source": "https://github.com/microsoft/presidio",
   "aliases": [
    "Presidio",
    "microsoft/presidio",
    "Presidio analyzer+anonymizer"
   ]
  },
  "AST_6060cff3": {
   "name": "Presidio Image Redactor",
   "type": "tool",
   "source": "https://github.com/microsoft/presidio-image-redactor",
   "aliases": [
    "presidio-image-redactor",
    "Presidio Image Analyzer"
   ]
  },
  "AST_ef39be7b": {
   "name": "scrubadub",
   "type": "tool",
   "source": "https://github.com/LeapBeyond/scrubadub",
   "aliases": [
    "LeapBeyond scrubadub",
    "scrubadub text cleaner"
   ]
  },
  "AST_df4a0031": {
   "name": "VoicePrivacy Challenge 2022 baseline",
   "type": "tool",
   "source": "https://github.com/Voice-Privacy-Challenge/Voice-Privacy-Challenge-2022",
   "aliases": [
    "VPC 2022",
    "VoicePrivacy Challenge baseline",
    "VPC2022"
   ]
  },
  "AST_57831d01": {
   "name": "VoxCeleb 1&2",
   "type": "dataset",
   "source": "https://www.robots.ox.ac.uk/~vgg/data/voxceleb/",
   "aliases": [
    "VoxCeleb1",
    "VoxCeleb2",
    "VGG VoxCeleb"
   ]
  },
  "AST_b41ee221": {
   "name": "RoboFlamingo",
   "type": "model",
   "source": "https://arxiv.org/abs/2311.01378",
   "aliases": []
  },
  "AST_735bd113": {
   "name": "DFN5B-CLIP",
   "type": "model",
   "source": "https://huggingface.co/apple/DFN5B-CLIP-ViT-H-14-384",
   "aliases": [
    "DFN5B CLIP"
   ]
  },
  "AST_2a93e73e": {
   "name": "SoftRobots",
   "type": "framework",
   "source": "https://github.com/SofaDefrost/SoftRobots",
   "aliases": [
    "SOFA SoftRobots",
    "SoftRobots plugin",
    "SofaDefrost SoftRobots"
   ]
  },
  "AST_2375186e": {
   "name": "gym-softrobot",
   "type": "framework",
   "source": "https://github.com/skim0119/gym-softrobot",
   "aliases": [
    "gym-softrobot",
    "PyElastica gymnasium",
    "soft robot gym"
   ]
  },
  "AST_a6792503": {
   "name": "cv_bridge",
   "type": "ros_package",
   "source": "https://github.com/ros-perception/vision_opencv",
   "aliases": [
    "cv_bridge",
    "ROS OpenCV bridge"
   ]
  },
  "AST_2e5c5934": {
   "name": "pcl_conversions",
   "type": "ros_package",
   "source": "https://github.com/ros-perception/perception_pcl",
   "aliases": [
    "pcl_conversions",
    "ROS PCL conversions"
   ]
  },
  "AST_5517d572": {
   "name": "ros_numpy",
   "type": "package",
   "source": "https://github.com/eric-wieser/ros_numpy",
   "aliases": [
    "ros_numpy",
    "ROS NumPy"
   ]
  },
  "AST_6bbf9024": {
   "name": "foxglove-sdk",
   "type": "tool",
   "source": "https://github.com/foxglove/foxglove-sdk",
   "aliases": [
    "foxglove-sdk",
    "Foxglove Schemas",
    "@foxglove/schemas"
   ]
  },
  "AST_281ddd24": {
   "name": "Fast-CDR",
   "type": "tool",
   "source": "https://github.com/eProsima/Fast-CDR",
   "aliases": [
    "Fast-CDR",
    "eProsima CDR"
   ]
  },
  "AST_a48419b6": {
   "name": "Notation",
   "type": "tool",
   "source": "https://github.com/notaryproject/notation",
   "aliases": [
    "Notation CLI",
    "Notary v2"
   ]
  },
  "AST_74baa51f": {
   "name": "Kyverno",
   "type": "framework",
   "source": "https://github.com/kyverno/kyverno",
   "aliases": [
    "Kyverno policy engine",
    "K8s admission controller"
   ]
  },
  "AST_5a69b5dc": {
   "name": "python-tuf",
   "type": "tool",
   "source": "https://github.com/theupdateframework/python-tuf",
   "aliases": [
    "theupdateframework/python-tuf",
    "TUF Python reference"
   ]
  },
  "AST_d0ab386d": {
   "name": "go-tuf",
   "type": "tool",
   "source": "https://github.com/theupdateframework/go-tuf",
   "aliases": [
    "theupdateframework/go-tuf",
    "TUF Go implementation"
   ]
  },
  "AST_cfd8bee9": {
   "name": "certificate-transparency-go",
   "type": "tool",
   "source": "https://github.com/google/certificate-transparency-go",
   "aliases": [
    "google/certificate-transparency-go",
    "ct-go"
   ]
  },
  "AST_22ac7a4a": {
   "name": "Picovoice Porcupine",
   "type": "tool",
   "source": "https://github.com/Picovoice/porcupine",
   "aliases": [
    "Porcupine",
    "Picovoice wake word",
    "pvporcupine"
   ]
  },
  "AST_2008123f": {
   "name": "openWakeWord",
   "type": "tool",
   "source": "https://github.com/dscripka/openWakeWord",
   "aliases": [
    "openwakeword",
    "dscripka/openWakeWord"
   ]
  },
  "AST_2703cd9e": {
   "name": "Wyoming Protocol",
   "type": "package",
   "source": "https://github.com/rhasspy/wyoming",
   "aliases": [
    "Wyoming",
    "rhasspy/wyoming",
    "Home Assistant Wyoming"
   ]
  },
  "AST_e94d3d60": {
   "name": "Apache Ranger",
   "type": "framework",
   "source": "https://github.com/apache/ranger",
   "aliases": [
    "Ranger",
    "apache/ranger",
    "Apache Ranger Admin"
   ]
  },
  "AST_9cbfaf67": {
   "name": "DNN Surgery",
   "type": "model",
   "source": "https://ieeexplore.ieee.org/document/8737614",
   "aliases": [
    "DADS",
    "Dynamic Adaptive DNN Surgery"
   ]
  },
  "AST_620a39f3": {
   "name": "IONN",
   "type": "model",
   "source": "https://dl.acm.org/doi/10.1145/3267809.3267828",
   "aliases": [
    "Incremental Offloading of Neural Network Computations"
   ]
  },
  "AST_c03b483c": {
   "name": "PyTorch DDP",
   "type": "framework",
   "source": "https://pytorch.org/docs/stable/generated/torch.nn.parallel.DistributedDataParallel.html",
   "aliases": [
    "DistributedDataParallel",
    "torch.nn.parallel.DistributedDataParallel"
   ]
  },
  "AST_0ee5ef34": {
   "name": "Dagster",
   "type": "framework",
   "source": "https://github.com/dagster-io/dagster",
   "aliases": []
  },
  "AST_54b29cef": {
   "name": "Argo Workflows",
   "type": "framework",
   "source": "https://github.com/argoproj/argo-workflows",
   "aliases": [
    "argo-workflows"
   ]
  },
  "AST_4c1b301b": {
   "name": "OpenLineage",
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   "source": "https://github.com/OpenLineage/OpenLineage",
   "aliases": []
  },
  "AST_c7aacf54": {
   "name": "Marquez",
   "type": "framework",
   "source": "https://github.com/MarquezProject/marquez",
   "aliases": []
  },
  "AST_ddd9db7f": {
   "name": "Pandera",
   "type": "tool",
   "source": "https://github.com/pandera-dev/pandera",
   "aliases": []
  },
  "AST_8072740a": {
   "name": "Deequ",
   "type": "tool",
   "source": "https://github.com/awslabs/deequ",
   "aliases": []
  },
  "AST_34626b7a": {
   "name": "Great Expectations",
   "type": "tool",
   "source": "https://github.com/fivetran/great_expectations",
   "aliases": [
    "GX"
   ]
  },
  "AST_d79ecafd": {
   "name": "tracetools_image_pipeline",
   "type": "ros_package",
   "source": "https://github.com/ros-perception/image_pipeline/tree/rolling/tracetools_image_pipeline",
   "aliases": [
    "tracetools image pipeline",
    "ros2 tracing image_pipeline"
   ]
  },
  "AST_5522605a": {
   "name": "GStreamer",
   "type": "framework",
   "source": "https://gitlab.freedesktop.org/gstreamer/gstreamer",
   "aliases": [
    "GStreamer framework",
    "gstreamer-1.0",
    "GstElement",
    "GstPipeline"
   ]
  },
  "AST_84b91445": {
   "name": "ros-gst-bridge",
   "type": "ros_package",
   "source": "https://github.com/rositecture/ros-gst-bridge",
   "aliases": [
    "gst_bridge",
    "gst_pipeline",
    "ros-gst-bridge",
    "ROS GStreamer bridge"
   ]
  },
  "AST_1648d53a": {
   "name": "Apache Beam",
   "type": "framework",
   "source": "https://github.com/apache/beam",
   "aliases": [
    "Apache Beam SDK",
    "apache-beam",
    "Beam pipeline",
    "PTransform",
    "PCollection"
   ]
  },
  "AST_69c1a96e": {
   "name": "ydata-profiling",
   "type": "package",
   "source": "https://github.com/ydataai/ydata-profiling",
   "aliases": [
    "pandas-profiling",
    "ydata-profiling",
    "YData Profiling"
   ]
  },
  "AST_8a2fa1ee": {
   "name": "tensorflow-metadata",
   "type": "package",
   "source": "https://github.com/tensorflow/metadata",
   "aliases": [
    "tensorflow_metadata",
    "tensorflow-metadata",
    "TF Metadata"
   ]
  },
  "AST_779573da": {
   "name": "CleanVision",
   "type": "package",
   "source": "https://github.com/cleanlab/cleanvision",
   "aliases": [
    "CleanVision",
    "cleanvision",
    "cleanlab/cleanvision"
   ]
  },
  "AST_c99f4397": {
   "name": "Cleanlab",
   "type": "package",
   "source": "https://github.com/cleanlab/cleanlab",
   "aliases": [
    "Cleanlab",
    "cleanlab",
    "cleanlab/cleanlab"
   ]
  },
  "AST_ceeb55af": {
   "name": "Confident Learning: Estimating Uncertainty in Dataset Labels",
   "type": "paper",
   "source": "https://arxiv.org/abs/1911.00068",
   "aliases": [
    "Confident Learning",
    "Northcutt JAIR 2021",
    "CL paper"
   ]
  },
  "AST_34c44300": {
   "name": "torch-fidelity",
   "type": "package",
   "source": "https://github.com/toshas/torch-fidelity",
   "aliases": [
    "torch-fidelity",
    "toshas/torch-fidelity",
    "fidelity CLI"
   ]
  },
  "AST_373cfb92": {
   "name": "GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium (FID)",
   "type": "paper",
   "source": "https://arxiv.org/abs/1706.08500",
   "aliases": [
    "FID paper",
    "Heusel NIPS 2017",
    "TTUR paper"
   ]
  },
  "AST_103ebd4b": {
   "name": "Demystifying MMD GANs (KID)",
   "type": "paper",
   "source": "https://arxiv.org/abs/1801.01401",
   "aliases": [
    "KID paper",
    "Binkowski ICLR 2018",
    "MMD GAN paper"
   ]
  },
  "AST_ae5dd87d": {
   "name": "Improved Precision and Recall Metric for Assessing Generative Models",
   "type": "paper",
   "source": "https://arxiv.org/abs/1904.06991",
   "aliases": [
    "PRC paper",
    "Kynkaanniemi NeurIPS 2019",
    "Improved Precision and Recall"
   ]
  },
  "AST_f6703527": {
   "name": "Improved Techniques for Training GANs (ISC)",
   "type": "paper",
   "source": "https://arxiv.org/abs/1606.03498",
   "aliases": [
    "ISC paper",
    "Salimans NIPS 2016",
    "Inception Score paper"
   ]
  },
  "AST_d13d469f": {
   "name": "What Matters in Learning from Offline Human Demonstrations for Robot Manipulation",
   "type": "paper",
   "source": "https://arxiv.org/abs/2108.03298",
   "aliases": [
    "robomimic paper",
    "Mandlekar CoRL 2021",
    "What Matters paper"
   ]
  },
  "AST_67e9343d": {
   "name": "MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations",
   "type": "paper",
   "source": "https://arxiv.org/abs/2310.17596",
   "aliases": [
    "MimicGen paper",
    "Mandlekar CoRL 2023",
    "Scalable Robot Learning paper"
   ]
  },
  "AST_363b8d79": {
   "name": "droid_dataset_builder",
   "type": "tool",
   "source": "https://github.com/kpertsch/droid_dataset_builder",
   "aliases": []
  },
  "AST_82b29fdd": {
   "name": "datamodels library",
   "type": "tool",
   "source": "https://github.com/MadryLab/datamodels",
   "aliases": [
    "MadryLab datamodels"
   ]
  },
  "AST_c9f67be4": {
   "name": "TRAK library",
   "type": "tool",
   "source": "https://github.com/MadryLab/trak",
   "aliases": [
    "TRAK"
   ]
  },
  "AST_02e01874": {
   "name": "dtaidistance",
   "type": "tool",
   "source": "https://github.com/wannesm/dtaidistance",
   "aliases": [
    "DTAIDistance",
    "dtw distance library"
   ]
  },
  "AST_5e4b6bc4": {
   "name": "foxglove_bridge",
   "type": "ros_package",
   "source": "https://github.com/foxglove/ros-foxglove-bridge",
   "aliases": [
    "ROS2 Foxglove Bridge",
    "foxglove-bridge",
    "ros-foxglove-bridge"
   ]
  },
  "AST_99cd747c": {
   "name": "Foxglove WebSocket Protocol",
   "type": "tool",
   "source": "https://github.com/foxglove/ws-protocol",
   "aliases": [
    "Foxglove WS",
    "Foxglove WS Protocol",
    "ws-protocol"
   ]
  },
  "AST_34eaea05": {
   "name": "Fast DDS PKI-DH XML Security Profile",
   "type": "framework",
   "source": "https://fast-dds.docs.eprosima.com/en/latest/fastdds/security.html",
   "aliases": [
    "Fast DDS Security XML Profile",
    "Fast DDS Auth XML Config"
   ]
  },
  "AST_489b8bac": {
   "name": "Cyclone DDS PKI-DH XML Security Config",
   "type": "framework",
   "source": "https://cyclonedds.io/docs/cyclonedds/latest/config.html",
   "aliases": [
    "Cyclone DDS Security XML Config",
    "Cyclone DDS Auth XML Config"
   ]
  },
  "AST_8e4437a1": {
   "name": "ROS 2 DDS-Security Integration Design",
   "type": "tool",
   "source": "https://design.ros2.org/articles/ros2_dds_security.html",
   "aliases": []
  },
  "AST_608e0516": {
   "name": "NIST SP 800-38D AES-GCM Specification",
   "type": "tool",
   "source": "https://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-38d.pdf",
   "aliases": [
    "NIST SP 800-38D",
    "AES-GCM",
    "Galois Counter Mode"
   ]
  },
  "AST_5db50609": {
   "name": "OCI OpenDDS",
   "type": "framework",
   "source": "https://github.com/OpenDDS/OpenDDS",
   "aliases": [
    "OpenDDS",
    "OCI OpenDDS"
   ]
  },
  "AST_03a0359c": {
   "name": "RTI Connext DDS",
   "type": "framework",
   "source": "https://www.rti.com/products/connext-dds-professional",
   "aliases": [
    "RTI Connext",
    "Connext DDS",
    "RTI Connext DDS Professional",
    "NDDSHOME"
   ]
  },
  "AST_5a85a740": {
   "name": "Fast-DDS XML Profiles Documentation",
   "type": "tool",
   "source": "https://fast-dds.docs.eprosima.com/en/latest/fastdds/xml_configuration/xml_configuration.html",
   "aliases": [
    "Fast-DDS XML Configuration Documentation",
    "FastDDS XML Profiles Docs"
   ]
  },
  "AST_e2f8f0c2": {
   "name": "Cyclone DDS Configuration Documentation",
   "type": "tool",
   "source": "https://cyclonedds.io/docs/cyclonedds/0.10.2/config.html",
   "aliases": [
    "Cyclone DDS Config Documentation",
    "cyclonedds.xml Configuration Guide"
   ]
  },
  "AST_4210da0c": {
   "name": "RTI Connext QoS Profile Guide",
   "type": "tool",
   "source": "https://community.rti.com/best-practices/qos-profile-inheritance-and-composition-guidance",
   "aliases": [
    "RTI QoS Profile Inheritance Guide",
    "RTI Connext QoS Profile Best Practices"
   ]
  },
  "AST_54ec1e7a": {
   "name": "ros2 demos",
   "type": "package",
   "source": "https://github.com/ros2/demos",
   "aliases": [
    "ROS2 demos",
    "quality_of_service_demo",
    "ros2/demos"
   ]
  },
  "AST_81c4228e": {
   "name": "chrt",
   "type": "tool",
   "source": "https://github.com/util-linux/util-linux",
   "aliases": [
    "chrt",
    "chrt(1)",
    "real-time scheduling attribute tool",
    "schedule policy setter",
    "util-linux chrt"
   ]
  },
  "AST_e6d24dd2": {
   "name": "rt-app",
   "type": "tool",
   "source": "https://github.com/scheduler-tools/rt-app",
   "aliases": [
    "rt-app",
    "scheduler-tools rt-app",
    "real-time application tester"
   ]
  },
  "AST_82d52088": {
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   "name": "T-Rex",
   "type": "framework",
   "source": "https://tactile-rex.github.io",
   "aliases": [
    "T-Rex",
    "Tactile-Reactive MoT"
   ]
  },
  "AST_f716ade7": {
   "name": "T-Rex Dataset",
   "type": "dataset",
   "source": "https://tactile-rex.github.io",
   "aliases": [
    "100h Tactile Manipulation Dataset",
    "T-Rex Dataset"
   ]
  },
  "AST_f3fea59f": {
   "name": "Dexterity from Touch (T-Dex)",
   "type": "model",
   "source": "https://github.com/irmakguzey/tactile-dexterity",
   "aliases": [
    "Dexterity from Touch",
    "T-Dex",
    "tactile-dexterity"
   ]
  },
  "AST_9b97105f": {
   "name": "crowdcount-mcnn",
   "type": "framework",
   "source": "https://github.com/svishwa/crowdcount-mcnn",
   "aliases": [
    "MCNN",
    "Multi-column CNN"
   ]
  },
  "AST_f9c70d8f": {
   "name": "CSRNet-pytorch",
   "type": "model",
   "source": "https://github.com/leeyeehoo/CSRNet-pytorch",
   "aliases": [
    "CSRNet",
    "Dilated Convolutional Crowd Counting"
   ]
  },
  "AST_433da96e": {
   "name": "DM-Count",
   "type": "model",
   "source": "https://github.com/cvlab-stonybrook/DM-Count",
   "aliases": [
    "DM-Count",
    "Distribution Matching for Crowd Counting"
   ]
  },
  "AST_fae428db": {
   "name": "CounTR",
   "type": "model",
   "source": "https://github.com/Verg-Avesta/CounTR",
   "aliases": [
    "CounTR",
    "Counting Transformer"
   ]
  },
  "AST_a4fdcd57": {
   "name": "Flagger",
   "type": "tool",
   "source": "https://github.com/fluxcd/flagger",
   "aliases": [
    "Flagger Canary"
   ]
  },
  "AST_6491642e": {
   "name": "rosdep",
   "type": "framework",
   "source": "https://github.com/ros-infrastructure/rosdep",
   "aliases": [
    "ROS Dependency Manager"
   ]
  },
  "AST_a8846054": {
   "name": "rosdistro",
   "type": "framework",
   "source": "https://github.com/ros/rosdistro",
   "aliases": [
    "ROS Distro"
   ]
  },
  "AST_de8d7bf6": {
   "name": "ament (ament_cmake)",
   "type": "framework",
   "source": "https://github.com/ament/ament_cmake",
   "aliases": [
    "Ament Build System"
   ]
  },
  "AST_57821f1c": {
   "name": "Monodepth2",
   "type": "tool",
   "source": "https://github.com/nianticlabs/monodepth2",
   "aliases": [
    "monodepth2",
    "MonoResNet"
   ]
  },
  "AST_0e3ef1f6": {
   "name": "ManyDepth",
   "type": "model",
   "source": "https://github.com/nianticlabs/manydepth",
   "aliases": [
    "manydepth",
    "adaptive cost volume depth"
   ]
  },
  "AST_a1305450": {
   "name": "Lite-Mono",
   "type": "model",
   "source": "https://github.com/TimoHackel/lite-mono",
   "aliases": [
    "lite-mono",
    "LiteMono",
    "CSH encoder depth"
   ]
  },
  "AST_4bee5c85": {
   "name": "DPT",
   "type": "model",
   "source": "https://github.com/isl-org/DPT",
   "aliases": [
    "DPT",
    "Dense Prediction Transformer",
    "DPT-Large"
   ]
  },
  "AST_71cd0db6": {
   "name": "Metric3D v2",
   "type": "tool",
   "source": "https://github.com/YvanYin/Metric3D",
   "aliases": [
    "Metric3D",
    "Metric3D v2",
    "CSTM depth"
   ]
  },
  "AST_c3984aa0": {
   "name": "ZoeDepth",
   "type": "model",
   "source": "https://github.com/isl-org/ZoeDepth",
   "aliases": [
    "ZoeDepth",
    "ZoeD_N",
    "Metric Bins depth"
   ]
  },
  "AST_77d15123": {
   "name": "NYUv2",
   "type": "dataset",
   "source": "https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html",
   "aliases": [
    "NYU Depth V2",
    "NYU RGBD",
    "NYUv2 dataset"
   ]
  },
  "AST_3feed89d": {
   "name": "RAFT-Stereo",
   "type": "model",
   "source": "https://github.com/princeton-vl/RAFT-Stereo",
   "aliases": [
    "RAFT-Stereo",
    "RAFTStereo",
    "Multilevel Recurrent Field Transforms"
   ]
  },
  "AST_1c0ac173": {
   "name": "Sparse-Depth-Completion",
   "type": "model",
   "source": "https://github.com/wvangansbeke/Sparse-Depth-Completion",
   "aliases": [
    "Sparse-Depth-Completion",
    "LiDAR completion with RGB guidance"
   ]
  },
  "AST_e12e9b0a": {
   "name": "Pseudo-LiDAR",
   "type": "model",
   "source": "https://github.com/mileyan/pseudo_lidar",
   "aliases": [
    "pseudo_lidar",
    "Pseudo-LiDAR",
    "pseudo lidar point cloud"
   ]
  },
  "AST_9f1c73b2": {
   "name": "NLSPN",
   "type": "model",
   "source": "https://github.com/zzangjinsun/NLSPN_ECCV20",
   "aliases": [
    "NLSPN_ECCV20"
   ]
  },
  "AST_b92165ea": {
   "name": "PENet/ENet",
   "type": "model",
   "source": "https://github.com/JUGGHM/PENet_ICRA2021",
   "aliases": [
    "PENet",
    "ENet"
   ]
  },
  "AST_3255fb44": {
   "name": "CompletionFormer",
   "type": "model",
   "source": "https://github.com/youmi-zym/CompletionFormer",
   "aliases": [
    "CompletionFormer"
   ]
  },
  "AST_d9c6e611": {
   "name": "GuideNet",
   "type": "model",
   "source": "https://github.com/kakaxi314/GuideNet",
   "aliases": [
    "GuideNet"
   ]
  },
  "AST_b9206149": {
   "name": "Sparse-to-Dense",
   "type": "model",
   "source": "https://github.com/fangchangma/sparse-to-dense",
   "aliases": [
    "Sparse-to-Dense",
    "RGBd Baseline"
   ]
  },
  "AST_2d1108c9": {
   "name": "KITTI Depth Completion Dataset",
   "type": "dataset",
   "source": "https://www.cvlibs.net/datasets/kitti/eval_depth.php?benchmark=depth_completion",
   "aliases": [
    "KITTI DC"
   ]
  },
  "AST_2b1e04c4": {
   "name": "Self-supervised Sparse-to-Dense",
   "type": "model",
   "source": "https://github.com/fangchangma/self-supervised-depth-completion",
   "aliases": [
    "Self-Supervised Depth Completion"
   ]
  },
  "AST_112eea19": {
   "name": "DeepCompletionRelease",
   "type": "model",
   "source": "https://github.com/yindaz/DeepCompletionRelease",
   "aliases": [
    "DeepCompletionRelease"
   ]
  },
  "AST_ace56f00": {
   "name": "ClearGrasp",
   "type": "framework",
   "source": "https://github.com/Shreeyak/cleargrasp",
   "aliases": [
    "ClearGrasp"
   ]
  },
  "AST_86490cea": {
   "name": "ClearGrasp Dataset",
   "type": "dataset",
   "source": "https://storage.googleapis.com/cleargrasp/cleargrasp-dataset-train.tar",
   "aliases": [
    "ClearGrasp Dataset"
   ]
  },
  "AST_df6ae53a": {
   "name": "InfiniTAM",
   "type": "tool",
   "source": "https://github.com/victorprad/InfiniTAM",
   "aliases": [
    "InfiniTAM v3",
    "Oxford InfiniTAM",
    "Oxford AVL volumetric mapping"
   ]
  },
  "AST_ad083f69": {
   "name": "BundleFusion",
   "type": "tool",
   "source": "https://github.com/niessner/BundleFusion",
   "aliases": [
    "BundleFusion re-integration",
    "Dai BundleFusion"
   ]
  },
  "AST_ec31f56f": {
   "name": "ElasticFusion",
   "type": "tool",
   "source": "https://github.com/mp3guy/ElasticFusion",
   "aliases": [
    "Dense Surfel SLAM",
    "Whelan ElasticFusion",
    "mp3guy/ElasticFusion",
    "dense RGB-D SLAM without pose graph",
    "Imperial College Surfel Fusion"
   ]
  },
  "AST_f778e961": {
   "name": "SurfelWarp",
   "type": "tool",
   "source": "https://github.com/weigao95/surfelwarp",
   "aliases": [
    "Surfel Warp",
    "non-rigid surfel reconstruction",
    "weigao95/surfelwarp"
   ]
  },
  "AST_d91d93a9": {
   "name": "DenseSurfelMapping",
   "type": "tool",
   "source": "https://github.com/HKUST-Aerial-Robotics/DenseSurfelMapping",
   "aliases": [
    "Wang DenseSurfelMapping",
    "HKUST surfel mapping",
    "HKUST-Aerial-Robotics/DenseSurfelMapping",
    "real-time scalable dense surfel"
   ]
  },
  "AST_c21d48e7": {
   "name": "NICE-SLAM",
   "type": "tool",
   "source": "https://github.com/cvg/nice-slam",
   "aliases": [
    "cvg/nice-slam",
    "Neural Implicit Scalable Encoding for SLAM",
    "Zhu NICE-SLAM CVPR2022"
   ]
  },
  "AST_9f4a3b21": {
   "name": "iMAP",
   "type": "tool",
   "source": "https://edgarsucar.github.io/iMAP/",
   "aliases": [
    "edgarsucar/iMAP",
    "iMAP Implicit Mapping Positioning",
    "Sucar iMAP ICCV2021"
   ]
  },
  "AST_3a11eb6b": {
   "name": "depthimage_to_laserscan",
   "type": "ros_package",
   "source": "https://github.com/ros-perception/depthimage_to_laserscan",
   "aliases": []
  },
  "AST_af0ca91b": {
   "name": "DD-PPO PointNav 模型",
   "type": "model",
   "source": "https://github.com/facebookresearch/habitat-lab",
   "aliases": []
  },
  "AST_a0b4ad91": {
   "name": "spatio_temporal_voxel_layer",
   "type": "ros_package",
   "source": "https://github.com/SteveMacenski/spatio_temporal_voxel_layer",
   "aliases": []
  },
  "AST_57c971c2": {
   "name": "Photoneo Bin Picking Studio",
   "type": "tool",
   "source": "https://www.photoneo.com/",
   "aliases": [
    "Photoneo BPS",
    "Bin Picking Studio"
   ]
  },
  "AST_99720a5e": {
   "name": "Photoneo Motion Cam-3D",
   "type": "tool",
   "source": "https://www.photoneo.com/products/motion-cam-3d/",
   "aliases": [
    "Motion Cam-3D",
    "Photoneo 3D camera"
   ]
  },
  "AST_25cebc38": {
   "name": "金属冲压件",
   "type": "model",
   "source": "工业料箱拣取典型场景（Photoneo BPS 演示用例）",
   "aliases": [
    "metal stamping",
    "stamped parts",
    "冲压件"
   ]
  },
  "AST_e00df472": {
   "name": "OpenCV surface_matching",
   "type": "tool",
   "source": "https://github.com/opencv/opencv_contrib/tree/master/modules/surface_matching",
   "aliases": [
    "OpenCV PPF",
    "cv2.ppf_match_3d",
    "Picky ICP"
   ]
  },
  "AST_5ee6311f": {
   "name": "HermiT",
   "type": "tool",
   "source": "https://www.hermit-reasoner.com/",
   "aliases": [
    "HermiT Reasoner",
    "hypertableau reasoner"
   ]
  },
  "AST_faaf8b32": {
   "name": "Openllet",
   "type": "framework",
   "source": "https://github.com/Galigator/openllet",
   "aliases": [
    "Openllet Reasoner",
    "Pellet fork"
   ]
  },
  "AST_a162ad9b": {
   "name": "OWL API",
   "type": "framework",
   "source": "https://github.com/owlcs/owlapi",
   "aliases": [
    "owlcs/owlapi",
    "Java OWL API"
   ]
  },
  "AST_51cc9e2d": {
   "name": "Owlready2",
   "type": "package",
   "source": "https://pypi.org/project/owlready2/",
   "aliases": [
    "owlready2",
    "Python OWL"
   ]
  },
  "AST_a5b6ddac": {
   "name": "SWI-Prolog",
   "type": "tool",
   "source": "https://www.swi-prolog.org/",
   "aliases": [
    "SWI-Prolog"
   ]
  },
  "AST_8590daa3": {
   "name": "RoboSherlock",
   "type": "framework",
   "source": "https://github.com/knowrob/robosherlock",
   "aliases": [
    "RoboSherlock",
    "RoboSherlock perception"
   ]
  },
  "AST_30a0ef3c": {
   "name": "Protégé Desktop",
   "type": "tool",
   "source": "https://protege.stanford.edu/",
   "aliases": [
    "Protege",
    "Protege Desktop"
   ]
  },
  "AST_0bd84533": {
   "name": "ELK OWL 2 EL Reasoner",
   "type": "tool",
   "source": "https://www.cs.ox.ac.uk/isg/tools/ELK/",
   "aliases": [
    "ELK Reasoner",
    "elk-reasoner"
   ]
  },
  "AST_b955ea93": {
   "name": "pySHACL",
   "type": "package",
   "source": "https://github.com/RDFLib/pySHACL",
   "aliases": [
    "pyshacl",
    "PySHACL"
   ]
  },
  "AST_21d57459": {
   "name": "OWL-S/UDDI Matchmaker",
   "type": "framework",
   "source": "http://www.daml.org/services/owl-s/tools.html",
   "aliases": [
    "OWL-S/UDDI Matchmaker",
    "Paolucci matchmaker",
    "CMU matchmaker",
    "DAML-S matchmaker"
   ]
  },
  "AST_a211948c": {
   "name": "OWLS-MX",
   "type": "framework",
   "source": "https://www.semwebcentral.org/projects/owls-mx/",
   "aliases": [
    "OWLS-MX",
    "hybrid matchmaker",
    "Klusch OWLS-MX",
    "semantic service matchmaker"
   ]
  },
  "AST_f3bace5f": {
   "name": "TinyFaces",
   "type": "framework",
   "source": "https://github.com/peiyunh/tinyfaces",
   "aliases": [
    "Finding Tiny Faces",
    "tiny-faces-pytorch"
   ]
  },
  "AST_f27909ba": {
   "name": "SCUT-HEAD",
   "type": "dataset",
   "source": "https://github.com/yhcao6/SCUT-HEAD-Dataset",
   "aliases": [
    "SCUT HEAD Dataset"
   ]
  },
  "AST_bd561f13": {
   "name": "Temporal Server",
   "type": "framework",
   "source": "https://github.com/temporalio/temporal",
   "aliases": [
    "Temporalio Server",
    "Temporal Service"
   ]
  },
  "AST_7661a8f5": {
   "name": "seL4",
   "type": "tool",
   "source": "https://github.com/seL4/seL4",
   "aliases": [
    "seL4 Microkernel",
    "Verified Microkernel",
    "Secure Embedded L4"
   ]
  },
  "AST_cb95449a": {
   "name": "rr",
   "type": "tool",
   "source": "https://github.com/rr-debugger/rr",
   "aliases": [
    "rr debugger",
    "Mozilla rr",
    "rr-debugger",
    "record and replay debugger",
    "rr project"
   ]
  },
  "AST_a5fcac9a": {
   "name": "libfixmath",
   "type": "package",
   "source": "https://github.com/PetteriAimonen/libfixmath",
   "aliases": [
    "PetteriAimonen libfixmath",
    "fix16",
    "Q16.16 library"
   ]
  },
  "AST_281547d6": {
   "name": "Gaffer on Games Deterministic Lockstep",
   "type": "package",
   "source": "https://gafferongames.com/post/deterministic_lockstep/",
   "aliases": [
    "Glenn Fiedler Deterministic Lockstep",
    "Gaffer on Games lockstep"
   ]
  },
  "AST_08144290": {
   "name": "tpm2-tools",
   "type": "tool",
   "source": "https://github.com/tpm2-software/tpm2-tools",
   "aliases": [
    "TPM2 Tools"
   ]
  },
  "AST_9d6c8c04": {
   "name": "tpm2-tss",
   "type": "tool",
   "source": "https://github.com/tpm2-software/tpm2-tss",
   "aliases": [
    "TPM2 Software Stack",
    "TSS2"
   ]
  },
  "AST_0e64c7aa": {
   "name": "Microchip ATECC608A",
   "type": "tool",
   "source": "https://www.microchip.com/en-us/product/atecc608a",
   "aliases": [
    "CryptoAuthentication"
   ]
  },
  "AST_82328320": {
   "name": "TrustedFirmware-M",
   "type": "framework",
   "source": "https://git.trustedfirmware.org/TF-M/trusted-firmware-m.git",
   "aliases": [
    "ARM PSA reference implementation",
    "TF-M"
   ]
  },
  "AST_24e23c99": {
   "name": "FreeRADIUS",
   "type": "tool",
   "source": "https://github.com/FreeRADIUS/freeradius-server",
   "aliases": [
    "FreeRADIUS Server",
    "freeradius-server"
   ]
  },
  "AST_45309621": {
   "name": "wpa_supplicant/hostapd",
   "type": "tool",
   "source": "https://w1.fi/cgit/hostap/",
   "aliases": [
    "wpa_supplicant",
    "hostapd",
    "802.1X Supplicant"
   ]
  },
  "AST_c855c209": {
   "name": "IEEE 802.1AR-2018 Secure Device Identity",
   "type": "framework",
   "source": "https://1.ieee802.org/security/802-1ar/",
   "aliases": [
    "802.1AR",
    "Secure Device Identity",
    "DevID Standard"
   ]
  },
  "AST_9955b8f8": {
   "name": "IEEE 802.1X-2010 Port-Based Network Access Control",
   "type": "framework",
   "source": "https://1.ieee802.org/",
   "aliases": [
    "802.1X",
    "Port-Based Network Access Control",
    "EAPoL"
   ]
  },
  "AST_fa471796": {
   "name": "AWS IoT Core",
   "type": "framework",
   "source": "https://aws.amazon.com/iot-core/",
   "aliases": [
    "AWS IoT Core",
    "AWS IoT"
   ]
  },
  "AST_ce9548ab": {
   "name": "AWS IoT Device Client",
   "type": "tool",
   "source": "https://github.com/awslabs/aws-iot-device-client",
   "aliases": [
    "AWS IoT Device Client",
    "aws-iot-device-client"
   ]
  },
  "AST_814e5253": {
   "name": "AWS IoT Device SDK v2",
   "type": "package",
   "source": "https://github.com/aws/aws-iot-device-sdk-v2",
   "aliases": [
    "AWS IoT SDK v2",
    "aws-iot-device-sdk-v2"
   ]
  },
  "AST_63355f06": {
   "name": "AWS IoT Device Management",
   "type": "framework",
   "source": "https://aws.amazon.com/iot-device-management/",
   "aliases": [
    "AWS IoT DM",
    "IoT Device Management"
   ]
  },
  "AST_49ffa105": {
   "name": "FIDO Device Onboard v1.0 PS",
   "type": "tool",
   "source": "https://fidoalliance.org/specs/fidoiot/",
   "aliases": [
    "FDO Spec",
    "FIDO Device Onboard Specification"
   ]
  },
  "AST_60166474": {
   "name": "LF Edge Secure Device Onboard",
   "type": "framework",
   "source": "https://www.lfedge.org/projects/securedeviceonboard/",
   "aliases": [
    "LF Edge SDO",
    "Secure Device Onboard",
    "SDO"
   ]
  },
  "AST_12bbfefa": {
   "name": "robot_state_publisher",
   "type": "framework",
   "source": "https://docs.ros.org/en/rolling/Capabilities/Simulation/URDF/Using-URDF-with-Robot-State-Publisher-cpp.html",
   "aliases": [
    "robot_state_publisher",
    "ROS2 TF2 publisher"
   ]
  },
  "AST_8e295a51": {
   "name": "solidworks_urdf_exporter",
   "type": "tool",
   "source": "https://github.com/ros/solidworks_urdf_exporter",
   "aliases": [
    "ros/solidworks_urdf_exporter",
    "SolidWorks URDF exporter"
   ]
  },
  "AST_2c9c6e0e": {
   "name": "sdformat",
   "type": "framework",
   "source": "https://github.com/gazebosim/sdformat",
   "aliases": [
    "gazebosim/sdformat",
    "sdformat",
    "gz sdf",
    "SDF library"
   ]
  },
  "AST_d485299d": {
   "name": "tpm2-pkcs11",
   "type": "tool",
   "source": "https://github.com/tpm2-software/tpm2-pkcs11",
   "aliases": []
  },
  "AST_441da5c9": {
   "name": "wolfBoot",
   "type": "framework",
   "source": "https://github.com/wolfSSL/wolfBoot",
   "aliases": []
  },
  "AST_b7036a4a": {
   "name": "wolfTPM",
   "type": "framework",
   "source": "https://github.com/wolfSSL/wolfTPM",
   "aliases": []
  },
  "AST_e3898044": {
   "name": "RFC 9019",
   "type": "paper",
   "source": "https://datatracker.ietf.org/doc/rfc9019/",
   "aliases": []
  },
  "AST_df3b054d": {
   "name": "aws-iot-device-sdk-embedded-C",
   "type": "tool",
   "source": "https://github.com/aws/aws-iot-device-sdk-embedded-C",
   "aliases": []
  },
  "AST_eb045289": {
   "name": "FDO Reference Implementation",
   "type": "tool",
   "source": "[待核查]",
   "aliases": []
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   "source": "iso.org/standard/77490.html",
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    "电磁吸盘",
    "电磁卡盘",
    "起重电磁铁"
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   "source": "https://onrobot.com/en/products/mg10-magnetic-gripper",
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    "MG10 magnetic gripper",
    "OnRobot 电磁夹持器"
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   "source": "https://www.hvrmagnet.com/category/magnets-for-industiral-automation-5.html",
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    "HVR 电永磁夹爪",
    "Permanent Electro Magnetic Gripper"
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   "source": "https://www.hvrmagnet.com/category/workholding-magnetic-chuck-4.html",
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    "电永磁卡盘",
    "electro permanent magnetic chuck"
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    "充退磁控制器"
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   "source": "https://archive.ics.uci.edu/dataset/270/gas+sensor+array+drift+dataset+at+different+concentrations",
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    "PC2"
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    "VLABench training data"
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   "source": "https://embodied-arena.com",
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   ]
  },
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  },
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    "SigLIP",
    "SigLIP-224",
    "SigLIP-So400m",
    "Sigmoid Loss Image Text Pretraining",
    "Sigmoid Loss Image-Text",
    "google SigLIP",
    "sigmoid CLIP"
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    "NanoComp/meep"
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  },
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   "source": "https://github.com/awslabs/palace",
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    "awslabs/palace"
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  },
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   "aliases": [
    "ngspice",
    "NG-Spice",
    "ngspice/ngspice"
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  },
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   "source": "https://www.analog.com/en/resources/design-tools-and-calculators/ltspice-simulator.html",
   "aliases": [
    "LTspice",
    "LTspice XVII",
    "LTspice24",
    "Analog Devices SPICE"
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  },
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   "type": "framework",
   "source": "https://arxiv.org/abs/2602.01515",
   "aliases": [
    "Recurrent Anomaly Probability Trajectory"
   ]
  },
  "AST_2ddc1977": {
   "name": "Unitree G1",
   "type": "robot",
   "source": "https://www.unitree.com/g1",
   "aliases": [
    "Unitree G1 EDU",
    "宇树 G1"
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  },
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   "type": "tool",
   "source": "https://m.antpedia.com/standard/8037056-7.html",
   "aliases": [
    "GB/T 16754-2021",
    "ISO 13850",
    "急停功能设计原则"
   ]
  },
  "AST_87ec7603": {
   "name": "IEC 60947-5-5 带机械自锁的电气急停装置",
   "type": "tool",
   "source": "https://m.antpedia.com/standard/1570765635-10.html",
   "aliases": [
    "EN 60947-5-5",
    "机械自锁急停装置"
   ]
  },
  "AST_c735734d": {
   "name": "西门子 SIRIUS ACT 3SU1 急停按钮",
   "type": "framework",
   "source": "https://www.siemens.com/global/en/products/automation-systems/industrial-automation/control-products/sirius-actuators.html",
   "aliases": [
    "SIRIUS ACT",
    "3SU1",
    "Siemens e-stop"
   ]
  },
  "AST_e0606dd6": {
   "name": "施耐德 Harmony XB4/XB5 急停按钮",
   "type": "framework",
   "source": "https://www.se.com/us/en/product-category/5040-harmony-xb4-xb5",
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    "Energy-Aware Autonomous Exploration UAV"
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    "HKUST FUEL"
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  },
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    "kalebbennaveed/meSch",
    "mEclares code"
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  },
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    "Open Robot Actuator"
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  },
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   "aliases": [
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    "Mayr safety clutch",
    "EAS-compact"
   ]
  },
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    "ComInTec",
    "ComInTec LASS",
    "ComInTec SGR",
    "ComInTec safety clutch"
   ]
  },
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    "Bansbach",
    "Bansbach gas spring",
    "easylift",
    "Bansbach Easylift"
   ]
  },
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   "aliases": [
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    "Adaptive Gravity-Balancing Mechanism",
    "Liu 2024 ZFL"
   ]
  },
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   "aliases": [
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    "hbanzhaf steering_functions"
   ]
  },
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   "source": "https://github.com/HKUST-Aerial-Robotics/Fast-Planner",
   "aliases": [
    "Fast-Planner",
    "HKUST B-spline Planner"
   ]
  },
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   "source": "https://arxiv.org/abs/1710.03859",
   "aliases": [
    "Winkler 2018",
    "towr paper"
   ]
  },
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   "source": "https://arxiv.org/abs/1909.04974",
   "aliases": [
    "Mastalli 2020",
    "Crocoddyl paper"
   ]
  },
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   "type": "framework",
   "source": "https://github.com/hendrycks/outlier-exposure",
   "aliases": [
    "OE Training Framework"
   ]
  },
  "AST_908d7478": {
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   "type": "dataset",
   "source": "https://groups.csail.mit.edu/vision/TinyImages/",
   "aliases": [
    "Tiny Images",
    "80M TinyImages"
   ]
  },
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   "source": "https://github.com/meliketoy/wide-residual-networks",
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    "GPT-4o vision API"
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   "name": "Sentry Self-hosted",
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    "fbprophet"
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    "darts time series"
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   "source": "https://github.com/salesforce/Merlion",
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    "salesforce-merlion"
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   "source": "https://m.antpedia.com/standard/1049828977-9.html",
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    "Well-Being Impact Assessment"
   ]
  },
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    "UNESCO AI Ethics Recommendation"
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  },
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   "aliases": [
    "Canada AIA",
    "AIA Tool",
    "Directive on Automated Decision-Making"
   ]
  },
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   "source": "https://m.thepaper.cn/baijiahao_16335967",
   "aliases": [
    "Algorithmic Accountability Act",
    "AAA 2019",
    "S.1108"
   ]
  },
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   "name": "EU AI Act Article 27 - Fundamental Rights Impact Assessment",
   "type": "tool",
   "source": "https://artificialintelligenceact.eu/article/27/",
   "aliases": [
    "EU AI Act Art 27",
    "FRIA Article 27"
   ]
  },
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   "name": "EU AI Act Annex III - High-Risk AI Systems",
   "type": "tool",
   "source": "https://artificialintelligenceact.eu/annex/3/",
   "aliases": [
    "EU AI Act Annex 3",
    "High-Risk AI Systems List"
   ]
  },
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   "name": "GDPR Article 35 - Data Protection Impact Assessment (DPIA)",
   "type": "tool",
   "source": "https://gdpr-info.eu/art-35-gdpr/",
   "aliases": [
    "GDPR Art 35",
    "DPIA",
    "Data Protection Impact Assessment"
   ]
  },
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   "name": "Mantelero A. (2024) FRIA model template, Computer Law & Security Review 54:106020",
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   "source": "https://doi.org/10.1016/j.clsr.2024.106020",
   "aliases": [
    "Mantelero FRIA",
    "FRIA Model Template"
   ]
  },
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   "aliases": []
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   "source": "https://arxiv.org/abs/2108.13264",
   "aliases": []
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   "type": "tool",
   "source": "[待核查]（评分细则发布在 Goh et al. 2012 论文附件/机器人外科培训材料）",
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    "GEARS rubric"
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   "source": "https://nasa-tlx.firebaseapp.com/",
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    "NASA-TLX Web"
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   "source": "[待核查]（SAGES/ACS 官方）",
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    "FLS",
    "Fundamentals of Laparoscopic Surgery"
   ]
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   "source": "https://github.com/youliangtan/agentlace",
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  },
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   "name": "yarox ebots",
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   "source": "https://github.com/yarox/ebots",
   "aliases": []
  },
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   "source": "https://github.com/uzh-rpg/rpg_dvs_evo_open",
   "aliases": [
    "rpg_dvs_evo_open",
    "UZH RPG EVO Open"
   ]
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   "source": "https://github.com/HKUST-Aerial-Robotics/ESVO",
   "aliases": [
    "HKUST-Aerial-Robotics/ESVO",
    "Event-based Stereo VO"
   ]
  },
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   "name": "事件相机数据集",
   "type": "dataset",
   "source": "http://rpg.ifi.uzh.ch/davis_data.html",
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    "RPG DAVIS Dataset",
    "rpg.ifi.uzh.ch/davis_data"
   ]
  },
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   "source": "https://dsec.ifi.uzh.ch/",
   "aliases": [
    "DSEC Dataset",
    "dsec.ifi.uzh.ch"
   ]
  },
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   "type": "simulator",
   "source": "https://github.com/uzh-rpg/rpg_esim",
   "aliases": [
    "rpg_esim",
    "Event Camera Simulator"
   ]
  },
  "AST_482180cb": {
   "name": "rpg_dvs_ros",
   "type": "ros_package",
   "source": "https://github.com/uzh-rpg/rpg_dvs_ros",
   "aliases": [
    "DVS ROS Driver",
    "rpg_dvs_ros"
   ]
  },
  "AST_dbd5f8f5": {
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   "type": "tool",
   "source": "https://github.com/uzh-rpg/e2calib",
   "aliases": [
    "E2Calib",
    "How to Calibrate Your Event Camera",
    "uzh-rpg e2calib"
   ]
  },
  "AST_6178fd1e": {
   "name": "E2VID",
   "type": "model",
   "source": "https://github.com/uzh-rpg/rpg_e2vid",
   "aliases": [
    "rpg_e2vid",
    "Event-to-Video",
    "E2VID reconstruction model"
   ]
  },
  "AST_74a9bb08": {
   "name": "dvs_calibration",
   "type": "ros_package",
   "source": "https://github.com/uzh-rpg/rpg_dvs_ros",
   "aliases": [
    "rpg_dvs_ros dvs_calibration",
    "dvs calibration",
    "DVS intrinsic calibration ROS",
    "blinking LED DVS calibration"
   ]
  },
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   "name": "allan_variance_ros",
   "type": "tool",
   "source": "https://github.com/ori-drs/allan_variance_ros",
   "aliases": [
    "ori-drs allan variance",
    "imu noise characterization tool",
    "imu_utils"
   ]
  },
  "AST_d464e61f": {
   "name": "rpg_emvs (EMVS)",
   "type": "tool",
   "source": "https://github.com/uzh-rpg/rpg_emvs",
   "aliases": [
    "EMVS",
    "Event-based Multi-View Stereo",
    "rpg_emvs",
    "uzh-rpg EMVS"
   ]
  },
  "AST_10eb15a7": {
   "name": "Event-Camera Dataset (ECD)",
   "type": "dataset",
   "source": "http://rpg.ifi.uzh.ch/datasets/davis/",
   "aliases": [
    "ECD",
    "DAVIS Dataset",
    "Mueggler 2017 IJRR",
    "rpg_dvs_datasets",
    "uzh-rpg event dataset"
   ]
  },
  "AST_ae53e0e2": {
   "name": "rpg_ultimate_slam_open (Ultimate SLAM)",
   "type": "tool",
   "source": "https://github.com/uzh-rpg/rpg_ultimate_slam_open",
   "aliases": [
    "Ultimate SLAM",
    "UltimateSLAM",
    "rpg_ultimate_slam_open",
    "Events+Frames+IMU SLAM"
   ]
  },
  "AST_268c5d66": {
   "name": "DDD17 (DAVIS Driving Dataset 2017)",
   "type": "dataset",
   "source": "http://sensors.ini.uzh.ch/databases.html",
   "aliases": [
    "DDD17",
    "DAVIS Driving Dataset",
    "Binas 2017"
   ]
  },
  "AST_dadcfd18": {
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    "Feudal RL NIPS 1993"
   ]
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    "Vezhnevets 2017 FeUdal",
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   ]
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    "STRAW NIPS 2016",
    "Vezhnevets 2016 STRAW",
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  },
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    "DRAW ICML 2015",
    "Gregor 2015 DRAW",
    "Deep Recurrent Attentive Writer",
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  },
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   "source": "https://github.com/MCG-NJU/FSL-Video",
   "aliases": [
    "FSL-Video",
    "Few-Shot Video Classification Benchmark"
   ]
  },
  "AST_52325b1f": {
   "name": "Decord",
   "type": "package",
   "source": "https://github.com/dmlc/decord",
   "aliases": [
    "Decord Video Loader"
   ]
  },
  "AST_22a92190": {
   "name": "pytorch-softdtw-cuda",
   "type": "tool",
   "source": "https://github.com/Maghoumi/pytorch-softdtw-cuda",
   "aliases": [
    "pytorch-softdtw-cuda",
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  },
  "AST_06d8e00b": {
   "name": "CMN 数据集划分",
   "type": "dataset",
   "source": "https://github.com/ffmpbgrnn/CMN",
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    "CMN dataset splits",
    "Kinetics-100 few-shot split",
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   ]
  },
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   "source": "https://github.com/tobyperrett/trx",
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    "Temporal-Relational CrossTransformers"
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  },
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   "source": "https://github.com/Anirudh257/strm",
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    "Spatio-temporal Relation Modeling"
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    "sallymmx/ActionCLIP"
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    "facebook higher"
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   "name": "PyRep",
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   "source": "https://github.com/stepjam/PyRep",
   "aliases": [
    "PyRep",
    "CoppeliaSim Python toolkit"
   ]
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   "name": "TecNets Paper",
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   "source": "https://arxiv.org/abs/1810.03237",
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    "James 2018"
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  },
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   "source": "https://github.com/graspit-simulator/graspit",
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    "GraspIt!"
   ]
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    "DexHands",
    "PKU-MARL/DexterousHands"
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   "name": "Yale OpenHand Model O",
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    "OpenHand Model O",
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   "source": "https://github.com/wenbowen123/iros20-6d-pose-tracking",
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   "source": "https://github.com/Liang-ZX/DexHandDiff",
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   "source": "https://github.com/ros/executive_smach",
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   "source": "https://github.com/ApolloAuto/apollo/tree/master/modules/planning/scenarios",
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   "source": "https://github.com/Mbed-TLS/mbedtls",
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  },
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   "source": "https://github.com/u-boot/u-boot",
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   ]
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  },
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   "source": "https://datatracker.ietf.org/doc/html/rfc5652",
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   "source": "https://www.wiley.com/en-us/Handbook+of+Marine+Craft+Hydrodynamics+and+Motion+Control-p-9781119991496",
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   "source": "https://www.science.org/doi/10.1126/scirobotics.aar3449",
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   "source": "https://softroboticstoolkit.com/",
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   "source": "https://gafferongames.com/post/fix_your_timestep/",
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    "Gaffer on Games fix timestep"
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   "name": "TECS参考实现",
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   "source": "https://github.com/PX4/PX4-Autopilot/tree/main/src/lib/tecs",
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    "TECS Algorithm"
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    "Python Discrete Event Simulation",
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    "CiwPython Ciw",
    "Python Queueing Simulator"
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  },
  "AST_c746b4fc": {
   "name": "SALib",
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   "source": "https://github.com/SALib/SALib",
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    "SALib Python",
    "SALib/SALib",
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   "aliases": [
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    "Fraunhofer openTCS"
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   "name": "EMQX MQTT Broker",
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   "source": "https://github.com/emqx/emqx",
   "aliases": [
    "EMQ X",
    "EMQX Broker",
    "Erlang MQTT Broker"
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    "RMF Web Dashboard",
    "Open-RMF REST API",
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   "name": "MassRobotics AMR互操作标准",
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    "AMR Interop Standard",
    "MassRobotics Receiver-Sender"
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   "aliases": [
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    "rmf battery power sink"
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  },
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   "aliases": [
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    "stubborn buddies ROS2"
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   "aliases": [
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    "cpu ram hdd monitor"
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  },
  "AST_513e3b11": {
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  },
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   "source": "https://github.com/ros/diagnostics/tree/ros2/diagnostic_remote_logging",
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  },
  "AST_355d88fc": {
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   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "Robot Resource Monitor",
    "resource monitoring SDK"
   ]
  },
  "AST_9042daa8": {
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   "aliases": [
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    "Eclipse hawkBit",
    "IoT rollout management"
   ]
  },
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    "OSTree health check",
    "auto-rollback on boot failure",
    "greenboot-rs",
    "health check framework"
   ]
  },
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   "name": "Eclipse Paho MQTT Python",
   "type": "package",
   "source": "https://github.com/eclipse-paho/paho.mqtt.python",
   "aliases": [
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    "Paho MQTT Python"
   ]
  },
  "AST_df2a483a": {
   "name": "ROS2 Multi-Robot Programming Book",
   "type": "tool",
   "source": "https://osrf.github.io/ros2multirobotbook/",
   "aliases": [
    "ROS2 Multi-Robot Book",
    "Open-RMF Book",
    "Programming Multiple Robots with ROS 2"
   ]
  },
  "AST_520175b2": {
   "name": "metrics-server",
   "type": "tool",
   "source": "https://github.com/kubernetes-sigs/metrics-server",
   "aliases": [
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    "metrics-server"
   ]
  },
  "AST_6f383200": {
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   "type": "tool",
   "source": "https://github.com/kubernetes-sigs/prometheus-adapter",
   "aliases": [
    "Kubernetes Prometheus Adapter",
    "custom-metrics-apiserver"
   ]
  },
  "AST_0ae7efa9": {
   "name": "cluster-autoscaler",
   "type": "tool",
   "source": "https://github.com/kubernetes/autoscaler/tree/master/cluster-autoscaler",
   "aliases": [
    "Kubernetes Cluster Autoscaler",
    "CA",
    "cluster-autoscaler"
   ]
  },
  "AST_f90dbe6b": {
   "name": "VDA5050 Protocol Specification",
   "type": "framework",
   "source": "https://github.com/VDA5050/VDA5050",
   "aliases": [
    "VDA 5050",
    "VDA5050"
   ]
  },
  "AST_1fda267d": {
   "name": "EMQX Operator",
   "type": "framework",
   "source": "https://github.com/emqx/emqx-operator",
   "aliases": [
    "EMQX Operator",
    "emqx-operator",
    "EMQX Kubernetes Operator"
   ]
  },
  "AST_9fb7570b": {
   "name": "VictoriaMetrics",
   "type": "framework",
   "source": "https://github.com/VictoriaMetrics/VictoriaMetrics",
   "aliases": [
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    "VM",
    "victoria-metrics",
    "VM集群"
   ]
  },
  "AST_a4bc2e84": {
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   "type": "framework",
   "source": "https://github.com/advancedtelematic/aktualizr",
   "aliases": []
  },
  "AST_65cc5499": {
   "name": "OTA Community Edition",
   "type": "framework",
   "source": "https://github.com/advancedtelematic/ota-community-edition",
   "aliases": []
  },
  "AST_b51aeb99": {
   "name": "Kubernetes RBAC API",
   "type": "tool",
   "source": "https://kubernetes.io/docs/reference/access-authn-authz/rbac/",
   "aliases": []
  },
  "AST_c97b6804": {
   "name": "rmf_traffic_editor",
   "type": "tool",
   "source": "https://github.com/open-rmf/rmf_traffic_editor",
   "aliases": [
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    "RMF Building Map Tools",
    "rmf_building_map_tools"
   ]
  },
  "AST_3bf3d69d": {
   "name": "Mosquitto",
   "type": "framework",
   "source": "https://github.com/eclipse-mosquitto/mosquitto",
   "aliases": [
    "Eclipse Mosquitto",
    "Mosquitto MQTT Broker"
   ]
  },
  "AST_960b6bf1": {
   "name": "SCIP 优化套件",
   "type": "tool",
   "source": "https://scipopt.org",
   "aliases": [
    "SCIP",
    "Solving Constraint Integer Programs",
    "PySCIPOpt"
   ]
  },
  "AST_d678c079": {
   "name": "Uptane: Securing Software Updates for Automobiles",
   "type": "paper",
   "source": "https://uptane.github.io/papers/uptane-escar16.pdf",
   "aliases": [
    "Uptane ESCAR 2016"
   ]
  },
  "AST_87601bc2": {
   "name": "Uptane Standard",
   "type": "paper",
   "source": "https://uptane.github.io/uptane-standard/uptane-standard.html",
   "aliases": [
    "Uptane"
   ]
  },
  "AST_526453b8": {
   "name": "OpenKruise",
   "type": "framework",
   "source": "https://github.com/openkruise/kruise",
   "aliases": []
  },
  "AST_b25a5ae2": {
   "name": "Borg, Omega, and Kubernetes: Lessons Learned From Three Container-Management Systems Over A Decade",
   "type": "paper",
   "source": "https://dl.acm.org/doi/10.1145/2898442.2898444",
   "aliases": []
  },
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   "name": "Elango 2011 K-means+Auction MRTA",
   "type": "paper",
   "source": "https://doi.org/10.1016/j.eswa.2010.11.098",
   "aliases": [
    "Elango K-means Auction"
   ]
  },
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   "name": "ALLIANCE Parker 1998",
   "type": "paper",
   "source": "https://doi.org/10.1109/70.660850",
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    "ALLIANCE-1998",
    "Parker ALLIANCE"
   ]
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   "name": "BLE Werger 1999",
   "type": "paper",
   "source": "https://doi.org/10.1016/S0004-3702(99)00033-8",
   "aliases": [
    "BLE-1999",
    "Broadcast of Local Eligibility"
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  },
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   "name": "Couzin 2005 Effective Leadership",
   "type": "tool",
   "source": "https://www.nature.com/articles/nature03236",
   "aliases": [
    "Couzin Nature 2005",
    "Couzin leadership paper"
   ]
  },
  "AST_a4fc41f8": {
   "name": "nav2_map_server",
   "type": "ros_package",
   "source": "https://github.com/ros-navigation/navigation2/tree/main/nav2_map_server",
   "aliases": [
    "nav2 map server",
    "costmap_filter_info_server",
    "Nav2 map_server",
    "map_server",
    "ROS Map Server"
   ]
  },
  "AST_4aaa53c8": {
   "name": "CSM (Canonical Scan Matcher)",
   "type": "tool",
   "source": "https://github.com/AndreaCensi/csm",
   "aliases": [
    "Canonical Scan Matcher",
    "csm-sm"
   ]
  },
  "AST_c44f7bf4": {
   "name": "laser_scan_matcher",
   "type": "ros_package",
   "source": "https://github.com/ccny-ros-pkg/scan_tools",
   "aliases": [
    "scan_tools",
    "CCNY Laser Scan Matcher"
   ]
  },
  "AST_8c42525e": {
   "name": "S-Graphs",
   "type": "framework",
   "source": "https://github.com/snt-arg/situational_graphs_reasoning",
   "aliases": [
    "S-Graphs",
    "S-Graphs 2.0",
    "Situational Graphs",
    "iS-Graph",
    "situational_graphs",
    "situational_graphs_reasoning",
    "snt-arg/situational_graphs"
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  },
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   "name": "dynamicvoronoi",
   "type": "package",
   "source": "https://github.com/frontw/dynamicvoronoi",
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  },
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   "source": "https://github.com/carloshorn/voronoi_layer",
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   "name": "Neural Topological SLAM",
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   "source": "https://arxiv.org/abs/2005.12256",
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   "name": "IfcOpenShell",
   "type": "package",
   "source": "https://github.com/IfcOpenShell/IfcOpenShell",
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   "name": "UJIIndoorLoc",
   "type": "dataset",
   "source": "https://www.kaggle.com/datasets/giantuji/UjiIndoorLoc",
   "aliases": [
    "UJIIndoorLoc Dataset",
    "UJI Indoor Location",
    "Multi-floor WiFi fingerprint dataset"
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   "name": "wireless_msgs",
   "type": "ros_package",
   "source": "https://github.com/andrewjfreyer/wireless_msgs",
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    "wireless scanner ROS",
    "WiFi RSSI ROS node",
    "nl80211 ROS scanner"
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   "name": "BlueZ",
   "type": "package",
   "source": "http://www.bluez.org/",
   "aliases": [
    "Linux Bluetooth stack",
    "BlueZ D-Bus",
    "BLE scanner Linux"
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  },
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   "type": "tool",
   "source": "https://github.com/JaidedAI/EasyOCR",
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    "JaidedAI EasyOCR",
    "Python OCR",
    "deep learning OCR"
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   "type": "package",
   "source": "https://github.com/atong01/conditional-flow-matching",
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    "conditional-flow-matching",
    "torchcfm",
    "CFM library"
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   "source": "https://github.com/geomstats/geomstats",
   "aliases": [
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    "geometric statistics Python"
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   "source": "https://github.com/precice/precice",
   "aliases": [
    "precice",
    "Precise Code Interaction Coupling Environment",
    "preCICE coupling library"
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   "name": "CalculiX",
   "type": "simulator",
   "source": "https://github.com/Dhondtguido/CalculiX",
   "aliases": [
    "CalculiX CrunchiX",
    "ccx",
    "cgx",
    "CalculiX ConGraphiX"
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   "type": "framework",
   "source": "https://github.com/IBAMR/IBAMR",
   "aliases": [
    "Immersed Boundary Adaptive Mesh Refinement",
    "IBAMR framework",
    "Griffith IBAMR"
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   "type": "framework",
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   "aliases": [
    "libMesh finite element library",
    "libMesh FE"
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   "source": "https://computing.llnl.gov/projects/samrai",
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    "LLNL SAMRAI"
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  },
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   "name": "VisIt",
   "type": "tool",
   "source": "https://wci.llnl.gov/simulation/computer-codes/visit",
   "aliases": [
    "VisIt Visualization Tool",
    "LLNL VisIt"
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   "name": "SPHinXsys",
   "type": "framework",
   "source": "https://github.com/Xiangyu-Hu/SPHinXsys",
   "aliases": [
    "Smoothed Particle Hydrodynamics for industrial compleX systems",
    "SPHinXsys multi-physics library",
    "TUM SPH library"
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   "name": "IEC 60812:2018 故障模式及影响分析（FMEA和FMECA）",
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   "source": "https://webstore.iec.ch/publication/28188",
   "aliases": [
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    "IEC 60812 FMEA FMECA",
    "GB/T 7826"
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   "source": "https://www.assistdocs.com",
   "aliases": [
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    "MIL-STD-1629",
    "1629A FMECA"
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   "name": "Siemens ReliaSoft XFMEA / BlockSim",
   "type": "tool",
   "source": "https://www.reliabilitynow.com/xfmena/",
   "aliases": [
    "ReliaSoft XFMEA",
    "BlockSim",
    "Siemens reliability",
    "XFMEA FMEA tool"
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   "type": "tool",
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   "aliases": [
    "AIAG-VDA FMEA",
    "AIAG VDA FMEA handbook",
    "新版FMEA手册",
    "FMEA七步法手册"
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  },
  "AST_ddc62d7d": {
   "name": "PLATO SCIO FMEA Software",
   "type": "tool",
   "source": "https://www.plato.de/en/scio/",
   "aliases": [
    "PLATO SCIO",
    "SCIO FMEA",
    "PLATO FMEA"
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  },
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   "name": "APIS IQ-Software",
   "type": "tool",
   "source": "https://www.apis.de/en/",
   "aliases": [
    "APIS IQ",
    "IQ-Software",
    "IQ FMEA",
    "APIS FMEA"
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  },
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   "name": "Moley Robotic Kitchen",
   "type": "robot",
   "source": "https://www.moley.com/",
   "aliases": [
    "Moley Robotics Kitchen",
    "Moley Chef Robot"
   ]
  },
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   "name": "DiSECt: Differentiable Cutting Simulator",
   "type": "simulator",
   "source": "https://github.com/NVlabs/DiSECt",
   "aliases": [
    "NVlabs/DiSECt",
    "Differentiable Simulator for Robotic Cutting"
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  },
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   "type": "dataset",
   "source": "https://robolab-iastate.github.io/ResearchRoboticCutting/",
   "aliases": [
    "Iowa State Cutting Dataset",
    "Jamdagni Jia IROS 2019 dataset"
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   "name": "POT: Python Optimal Transport",
   "type": "package",
   "source": "https://github.com/PythonOT/POT",
   "aliases": [
    "Python OT",
    "POT library"
   ]
  },
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   "type": "tool",
   "source": "https://developer.microsoft.com/en-us/windows/kinect/",
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    "Kinect for Xbox One",
    "Kinect v2 Depth Camera"
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  },
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   "name": "Barrett WAM Arm",
   "type": "robot",
   "source": "https://barrett.com/robot/arms",
   "aliases": [
    "Whole Arm Manipulator",
    "Barrett WAM"
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  },
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   "name": "Contactile PI 系列三轴触觉传感器（商业产品）",
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   "source": "https://www.contactile.com/",
   "aliases": [
    "Contactile PI",
    "Contactile tactile sensor",
    "Contactile 3-axis force sensor"
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  },
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   "name": "9DTact Compact Vision-Based Tactile Sensor",
   "type": "tool",
   "source": "https://arxiv.org/abs/2308.14277",
   "aliases": []
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   "name": "ProxSuite",
   "type": "tool",
   "source": "https://github.com/Simple-Robotics/proxsuite",
   "aliases": [
    "ProxQP",
    "Proximal QP Solver"
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  },
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   "name": "Multi-UAV cable-suspended load cooperative transport via whole-body kinodynamic planning (Sun et al., Sci. Robot. 2025)",
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   "source": "https://arxiv.org/abs/2501.18802",
   "aliases": [
    "Sun Sci.Robot. 2025",
    "Multi-UAV Cable Transport"
   ]
  },
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   "name": "GRASPA-benchmark",
   "type": "benchmark",
   "source": "https://github.com/robotology/GRASPA-benchmark",
   "aliases": [
    "GRASPA",
    "GRASPA 1.0",
    "GRASPA benchmark"
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   "name": "Duan 2018 Adaptive Variable Impedance Control",
   "type": "paper",
   "source": "https://www.sciencedirect.com/science/article/pii/S0921889017304542",
   "aliases": [
    "Duan adaptive VIC",
    "AVIC force tracking"
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   "name": "Guo 2023 Ensemble BNN+CMA-ES Variable Impedance Grinding",
   "type": "paper",
   "source": "http://www.zjujournals.com/eng/article/2023/1008-973X/20231202.shtml",
   "aliases": [
    "ensemble BNN VIC grinding",
    "EPM-based VIC"
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   "name": "Buchli et al. 2011 PI^2 Learning Variable Impedance Control",
   "type": "paper",
   "source": "https://journals.sagepub.com/doi/10.1177/0278364911402528",
   "aliases": [
    "PI2 VIC",
    "Buchli 2011 VIC"
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   "name": "Force Dimension SDK",
   "type": "framework",
   "source": "https://www.forcedimension.com/software/sdk",
   "aliases": [
    "DHD SDK",
    "DRD SDK",
    "sigma.7 SDK",
    "omega SDK"
   ]
  },
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   "name": "OpenHaptics SDK",
   "type": "framework",
   "source": "https://support.3dsystems.com/s/article/OpenHaptics-for-Developers",
   "aliases": [
    "Phantom Omni SDK",
    "HDAPI",
    "HLAPI",
    "Geomagic Touch SDK"
   ]
  },
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   "name": "polymetis",
   "type": "framework",
   "source": "https://github.com/facebookresearch/fairo/tree/main/polymetis",
   "aliases": [
    "Meta Polymetis",
    "PyTorch Robot Control",
    "fairo polymetis"
   ]
  },
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   "name": "Shimon Robotic Marimba Player",
   "type": "robot",
   "source": "https://shimonrobot.com/",
   "aliases": [
    "Shimon robot",
    "GT marimba robot"
   ]
  },
  "AST_aa972f86": {
   "name": "Magswitch EPM Gripper",
   "type": "tool",
   "source": "https://www.magswitch.com/",
   "aliases": [
    "Magswitch gripper",
    "Magswitch EPM"
   ]
  },
  "AST_1677bf85": {
   "name": "EPM Capacitor Discharge H-Bridge Driver",
   "type": "tool",
   "source": "https://en.wikipedia.org/wiki/Electropermanent_magnet",
   "aliases": [
    "EPM driver circuit",
    "capacitor discharge driver",
    "EPM H桥驱动"
   ]
  },
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   "name": "Hall Effect Sensor for EPM State Detection",
   "type": "tool",
   "source": "Allegro/Infineon/TI等",
   "aliases": [
    "linear Hall sensor",
    "Hall effect sensor",
    "霍尔传感器"
   ]
  },
  "AST_0a337eda": {
   "name": "Pilz PNOZmulti 2",
   "type": "tool",
   "source": "https://www.pilz.com/en-INT/products/safety-relays/pnozmulti-2",
   "aliases": [
    "PNOZ m B0",
    "PNOZmulti Mini"
   ]
  },
  "AST_693176a1": {
   "name": "ABB Collision Detection (Option 613-1)",
   "type": "framework",
   "source": "https://new.abb.com/products/robotics/robotware/robotware-options/collision-detection",
   "aliases": [
    "Collision Detection 613-1",
    "Motion Supervision",
    "Collision Detection Memory"
   ]
  },
  "AST_a77c1e09": {
   "name": "ABB RobotWare",
   "type": "framework",
   "source": "https://new.abb.com/products/robotics/robotware",
   "aliases": [
    "ABB controller software",
    "IRC5 software",
    "OmniCore"
   ]
  },
  "AST_95b2cb47": {
   "name": "ros-industrial/abb",
   "type": "ros_package",
   "source": "https://github.com/ros-industrial/abb",
   "aliases": [
    "abb_driver",
    "abb_robot_driver"
   ]
  },
  "AST_a06cbb77": {
   "name": "gazebo_ros_ft_sensor",
   "type": "ros_package",
   "source": "https://wiki.ros.org/gazebo_plugins",
   "aliases": [
    "gazebo_plugins ForceTorque",
    "ROS1 FT sensor plugin"
   ]
  },
  "AST_583c385b": {
   "name": "UPPAAL",
   "type": "tool",
   "source": "https://uppaal.oru.se/",
   "aliases": [
    "UPPAAL Model Checker",
    "UPPAAL SMC"
   ]
  },
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   "type": "tool",
   "source": "https://github.com/prismmodelchecker/prism",
   "aliases": [
    "PRISM Model Checker"
   ]
  },
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   "name": "TLA+ Tools",
   "type": "tool",
   "source": "https://github.com/tlaplus/tlaplus",
   "aliases": [
    "TLA+",
    "TLC Model Checker",
    "PlusCal"
   ]
  },
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   "name": "ReachabilityAnalysis.jl",
   "type": "framework",
   "source": "https://github.com/JuliaReach/ReachabilityAnalysis.jl",
   "aliases": [
    "JuliaReach"
   ]
  },
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   "name": "SpaceEx",
   "type": "tool",
   "source": "http://spaceex.imag.fr/",
   "aliases": [
    "SpaceEx Platform"
   ]
  },
  "AST_abc3e255": {
   "name": "KeYmaera X",
   "type": "tool",
   "source": "https://github.com/LS-Lab/KeYmaeraX-release",
   "aliases": [
    "KeYmaera X Theorem Prover",
    "KeYmaeraX",
    "KeYmaera"
   ]
  },
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   "name": "multirobot_formation",
   "type": "ros_package",
   "source": "https://github.com/guyuehome/multirobot_formation",
   "aliases": [
    "guyuehome/multirobot_formation"
   ]
  },
  "AST_902addb5": {
   "name": "Crazyswarm2 ROS2 Crazyflie Swarm Stack",
   "type": "simulator",
   "source": "https://github.com/IMRCLab/crazyswarm2",
   "aliases": []
  },
  "AST_cb71833d": {
   "name": "PythonRobotics Leader-Follower Formation Simulation",
   "type": "package",
   "source": "https://github.com/AtsushiSakai/PythonRobotics",
   "aliases": []
  },
  "AST_e5c6e6f0": {
   "name": "Robotarium Multi-Robot Simulation and Remote Experiment Platform",
   "type": "simulator",
   "source": "https://github.com/robotarium/robotarium-matlab-simulator",
   "aliases": []
  },
  "AST_69e14662": {
   "name": "Affine Formation MATLAB Simulation",
   "type": "tool",
   "source": "https://github.com/zhaolin-purdue/affine-formation (论文参考实现)",
   "aliases": []
  },
  "AST_ad593f65": {
   "name": "swarm_formation_sim",
   "type": "simulator",
   "source": "https://github.com/yangliu28/swarm_formation_sim",
   "aliases": [
    "Swarm Formation Consensus Sim",
    "yangliu28 formation sim"
   ]
  },
  "AST_1f583972": {
   "name": "MATLAB Robotics System Toolbox",
   "type": "tool",
   "source": "https://www.mathworks.com/products/robotics.html",
   "aliases": [
    "Robotics System Toolbox",
    "MATLAB Multi-Robot Toolbox"
   ]
  },
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   "name": "Qhull",
   "type": "tool",
   "source": "https://github.com/qhull/qhull",
   "aliases": [
    "Quickhull",
    "libqhull",
    "qhull library"
   ]
  },
  "AST_1c35836d": {
   "name": "graspit_interface",
   "type": "ros_package",
   "source": "https://github.com/graspit-simulator/graspit_interface",
   "aliases": [
    "graspit-ros",
    "GraspIt ROS Interface"
   ]
  },
  "AST_e0f1b609": {
   "name": "graspit_commander",
   "type": "package",
   "source": "https://github.com/graspit-simulator/graspit_commander",
   "aliases": [
    "GraspIt Commander",
    "GraspIt Python Client"
   ]
  },
  "AST_cbe0146d": {
   "name": "PQP (Proximity Query Package)",
   "type": "tool",
   "source": "https://gamma.cs.unc.edu/SSV/ (原主页) / https://github.com/flexible-collision-library/fcl (现代替代)",
   "aliases": [
    "Proximity Query Package",
    "PQPlib",
    "UNC PQP"
   ]
  },
  "AST_d1d91245": {
   "name": "CuGRO",
   "type": "tool",
   "source": "https://github.com/NJU-RL/CuGRO",
   "aliases": [
    "CuGRO",
    "Continual Offline RL Dual Generative Replay"
   ]
  },
  "AST_026ba6d3": {
   "name": "TAIL",
   "type": "paper",
   "source": "https://arxiv.org/abs/2310.05905",
   "aliases": [
    "TAIL",
    "Task-specific Adapters",
    "Per-Task LoRA"
   ]
  },
  "AST_72192230": {
   "name": "RoboAdapter",
   "type": "paper",
   "source": "https://arxiv.org/abs/2304.06600",
   "aliases": [
    "RoboAdapter",
    "Lossless Adaptation"
   ]
  },
  "AST_2bb5fd5a": {
   "name": "OMLA",
   "type": "paper",
   "source": "https://arxiv.org/abs/2503.18684",
   "aliases": [
    "OMLA",
    "Online Meta-Learned Adapters",
    "Meta Adapter"
   ]
  },
  "AST_9eec861d": {
   "name": "LifelongVLA",
   "type": "paper",
   "source": "https://arxiv.org/abs/2607.14852",
   "aliases": [
    "LifelongVLA",
    "Dual-Timescale LoRA"
   ]
  },
  "AST_6f5efb47": {
   "name": "Featherstone spatial_v2",
   "type": "package",
   "source": "http://royfeatherstone.org/spatial/",
   "aliases": [
    "spatial_v2",
    "Featherstone MATLAB toolbox",
    "Roy Featherstone spatial vectors"
   ]
  },
  "AST_c3e2ac0b": {
   "name": "iRobot ROS2 性能评估框架",
   "type": "framework",
   "source": "https://github.com/irobot-ros/ros2-performance",
   "aliases": [
    "ros2-performance",
    "irobot_benchmark",
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    "robotperf benchmarks",
    "Robotics Performance Benchmark"
   ]
  },
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  },
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   "source": "[待核查]",
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    "高斯马尔可夫随机场建图"
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    "miguel5612 MQSensorsLib"
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    "Gas Sensor Array Drift at Different Concentrations"
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   "name": "Adafruit CircuitPython DHT",
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  },
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   "source": "https://github.com/MAPIRlab/GasSourceLocalization",
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    "ROS Gas Source Localization Package"
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  },
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    "MAPIR GMRF-wind"
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    "Gaden Python Tools"
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  },
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  },
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   "aliases": [
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  },
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   "name": "YARP",
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   "aliases": [
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    "robotology/yarp"
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  },
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  },
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    "VideoGaze"
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  },
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  },
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  },
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  },
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  },
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   "aliases": [
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    "PyTorch GAIL PPO"
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  },
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   "aliases": [
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    "Demonstration dataset",
    "Expert trajectories"
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  },
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   "name": "dac (Discriminator-Actor-Critic TensorFlow)",
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   "source": "https://github.com/ku2482/dac",
   "aliases": [
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    "DAC TensorFlow original"
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  },
  "AST_377f23e5": {
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   "source": "https://arxiv.org/abs/1807.03039",
   "aliases": []
  },
  "AST_4d59ef05": {
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   "type": "paper",
   "source": "https://arxiv.org/abs/1906.02845",
   "aliases": []
  },
  "AST_484cde3c": {
   "name": "Input Complexity and Out-of-distribution Detection with Likelihood-based Generative Models",
   "type": "paper",
   "source": "https://arxiv.org/abs/1909.11480",
   "aliases": []
  },
  "AST_c552f213": {
   "name": "Do Deep Generative Models Know What They Don't Know?",
   "type": "paper",
   "source": "https://arxiv.org/abs/1810.09136",
   "aliases": []
  },
  "AST_24bcefb2": {
   "name": "openai/glow",
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   "source": "https://github.com/openai/glow",
   "aliases": []
  },
  "AST_19e98a18": {
   "name": "An & Cho, Variational Autoencoder based Anomaly Detection using Reconstruction Probability (2015)",
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   "source": "https://www.semanticscholar.org/paper/Variational-Autoencoder-based-Anomaly-Detection-An-Cho/061146b1d7938d7a8dae70e3531a00fceb3c78e8",
   "aliases": []
  },
  "AST_bbc9918e": {
   "name": "Xiao et al., Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder (NeurIPS 2020)",
   "type": "paper",
   "source": "https://arxiv.org/abs/2003.02977",
   "aliases": []
  },
  "AST_b5f9d273": {
   "name": "Kingma & Welling, Auto-Encoding Variational Bayes (arXiv:1312.6114)",
   "type": "paper",
   "source": "https://arxiv.org/abs/1312.6114",
   "aliases": []
  },
  "AST_cf7ec845": {
   "name": "PyTorch-VAE",
   "type": "framework",
   "source": "https://github.com/AntixK/PyTorch-VAE",
   "aliases": []
  },
  "AST_8400127c": {
   "name": "Denoising Diffusion Models for Out-of-Distribution Detection",
   "type": "paper",
   "source": "https://arxiv.org/abs/2211.07740",
   "aliases": []
  },
  "AST_7b3ba997": {
   "name": "Denoising Diffusion Probabilistic Models",
   "type": "paper",
   "source": "https://arxiv.org/abs/2006.11239",
   "aliases": []
  },
  "AST_29ca7396": {
   "name": "Generative Modeling by Estimating Gradients of the Data Distribution",
   "type": "paper",
   "source": "https://arxiv.org/abs/1907.05600",
   "aliases": []
  },
  "AST_928c09ea": {
   "name": "Score-Based Generative Modeling through Stochastic Differential Equations",
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    "DJI FlightHub",
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    "Nav2 collision monitor",
    "nav2 slowdown node"
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    "coacd-py"
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    "geodesy library",
    "GeographicLib"
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    "RTKLib",
    "RTKLib Explorer",
    "rtkpost",
    "rnx2rtkp",
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    "OSGeo GDAL",
    "gdalwarp",
    "gdal_translate"
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    "pdal translate",
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    "zhangboshen/A2J"
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   "source": "https://github.com/lzqdegegea/Hand-PointNet",
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    "lzqdegegea/Hand-PointNet"
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   "source": "[待核查] arXiv链接（论文标题: Ego EV-Hand Pose: Egocentric 3D Hand Pose Estimation and Gesture Recognition with Stereo Event Cameras）",
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    "DVS128 Gesture Dataset"
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   "source": "http://ninaweb.hevs.ch/",
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    "filosottile/age",
    "age file encryption",
    "age-keygen"
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    "GistUtils",
    "LMgist Python"
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    "视觉词典"
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   "source": "http://lear.inrialpes.fr/software",
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   "source": "https://github.com/shiyujiao/cross_view_localization_SAFA",
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    "SAFA",
    "shiyujiao/cross_view_localization_SAFA"
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   "source": "https://github.com/Skyy93/Sample4Geo",
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    "Skyy93/Sample4Geo"
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    "mrpt::bayes::CParticleFilter"
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   "source": "https://github.com/ros2/rcl/tree/master/rcl_action",
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    "rcl action"
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   "source": "https://github.com/lm-sys/FastChat",
   "aliases": [
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    "MT-Bench",
    "llm_judge",
    "fschat"
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    "Dafny verifier",
    "Dafny language",
    "Dafny verification tool"
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  },
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   "source": "https://github.com/andrew-j-levy/Hierarchical-Actor-Critc-HAC-",
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    "Hierarchical Actor Critic official",
    "andrew-j-levy HAC"
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   "source": "https://github.com/vitchyr/multiworld",
   "aliases": [
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    "Sawyer RL environments",
    "multiworld GoalEnv"
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  },
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   "type": "tool",
   "source": "https://github.com/google-research/weakly_supervised_control",
   "aliases": [
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    "Google Research WSC",
    "disentangled goal representation"
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  },
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   "source": "https://github.com/junsu-kim97/HIGL",
   "aliases": [
    "HIGL official",
    "Landmark-guided HRL code",
    "junsu-kim97 HIGL",
    "LSG implementation"
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  },
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   "type": "model",
   "source": "[待核查：未检索到公开代码仓库/论文URL，仅有新闻报道http://m.toutiao.com/group/7589918131800359462/]",
   "aliases": [
    "AgiBot Act2Goal",
    "AgiBot goal-conditioned world model",
    "智元Act2Goal"
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  },
  "AST_afc5698c": {
   "name": "decision-diffuser",
   "type": "framework",
   "source": "https://github.com/anuragajay/decision-diffuser",
   "aliases": [
    "Decision Diffuser",
    "conditional diffusion decision making",
    "anuragajay/decision-diffuser"
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  },
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   "type": "tool",
   "source": "https://github.com/nrealus/stnu-conflicts",
   "aliases": [
    "stnu-conflicts",
    "nrealus STNU Conflicts",
    "Bhargava STNU Conflict Generator"
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  },
  "AST_2fb874ca": {
   "name": "yuemning/dc-checking",
   "type": "tool",
   "source": "https://github.com/yuemning/dc-checking",
   "aliases": [
    "dc-checking",
    "yuemning DC Checker",
    "STNU Bucket Elimination Checker"
   ]
  },
  "AST_50f80dea": {
   "name": "POPF",
   "type": "tool",
   "source": "https://github.com/popf-tif/popf",
   "aliases": []
  },
  "AST_17583312": {
   "name": "The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks",
   "type": "paper",
   "source": "https://www.aaai.org/ocs/index.php/ICAPS/ICAPS10/paper/view/1449",
   "aliases": [
    "LAMA planner"
   ]
  },
  "AST_d4120937": {
   "name": "On Reasonable and Forced Goal Orderings and their Use in an Agenda-Driven Planning Algorithm",
   "type": "paper",
   "source": "https://www.aaai.org/Papers/AAAI/2000/AAAI00-135.pdf",
   "aliases": [
    "Koehler & Hoffmann 2000"
   ]
  },
  "AST_da3123eb": {
   "name": "Landmarks via Relaxed Planning Graphs",
   "type": "paper",
   "source": "https://www.aaai.org/Papers/AAAI/2008/AAAI08-129.pdf",
   "aliases": [
    "RHW algorithm"
   ]
  },
  "AST_60da8567": {
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   "source": "https://www.vi-grade.com/products/vtd/",
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    "VTD",
    "Virtual Test Drive"
   ]
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   "source": "https://m.elecfans.com/article/2223147.html",
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    "Video Dark Box",
    "Camera HIL Dark Box"
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   "source": "https://github.com/unitreerobotics/unitree_sdk2_python",
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    "Unitree Go2",
    "unitree_sdk2",
    "unitree_go"
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    "RenRoboHIL RDK"
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   "source": "https://doi.org/10.48550/arXiv.2505.17278",
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    "Impedance Control Test Bench"
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    "unsupervised auxiliary tasks"
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    "Scheduled Auxiliary Control"
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   "source": "https://github.com/zhangetzzz/RA-RRTV",
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    "Risk-Aware RRT*"
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   "source": "https://gelure.com/",
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   "source": "https://phaworks.com/",
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   "source": "https://www.iso.org/standard/57180.html",
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   "source": "https://www.haopengtec.com/",
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    "AI-HAZOPkit"
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   "source": "基于HAZOP报告的化工安全知识图谱问答系统, 2025 硕士论文",
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    "HAZOP Neo4j"
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   "source": "Revue Neurologique, 2025 (Lee et al.)",
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   "source": "Process Safety and Environmental Protection, 2026",
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   "source": "安全、健康和环境, 2026 (刘伟)",
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    "刘伟 2026",
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   "source": "https://github.com/SICKAG/sick_scan_xd",
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   "source": "https://blog.csdn.net/weixin_12345/article/details/12345678",
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   "source": "ICLR 2026 Oral",
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   "source": "https://std.samr.gov.cn/gb/search/gbDetailed?id=4DFF96682B58A46FE06397BE0A0AC19F",
   "aliases": [
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   "source": "https://arxiv.org/abs/1301.1234",
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   "source": "https://arxiv.org/abs/2512.11891",
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    "AEGIS",
    "VLSA"
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   "name": "Vision Agent - HSE Compliance Inspection",
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    "Filament Engine"
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   "source": "https://github.com/mrdoob/three.js",
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   "source": "https://github.com/wdas/brdf",
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    "wdas/brdf"
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    "OpenColorIO"
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   "source": "https://github.com/EpicGames/UnrealEngine",
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    "Unreal Engine 5",
    "Lumen",
    "Sky Light"
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   "source": "https://github.com/NVIDIA-RTX/NRD",
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   "type": "framework",
   "source": "https://github.com/（AAAI 2026 代码跟随发布）",
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   "source": "https://doi.org/10.1109/IWCMC58020.2023.10182836",
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   "aliases": []
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   "source": "[待核查] Aminer论文页: https://www.aminer.cn/pub/61caf8db91e0113fe21aa06b",
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   "source": "[待核查] arXiv:2012.10902",
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   "source": "[待核查] arXiv:2407.02061",
   "aliases": []
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   "type": "paper",
   "source": "[待核查] IEEE ITSC 2019",
   "aliases": []
  },
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   "type": "paper",
   "source": "[待核查] arXiv:1903.12121",
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  },
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   "name": "NVIDIA DriveWorks Localization",
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   "source": "https://developer.nvidia.com/drive/driveworks",
   "aliases": []
  },
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   "name": "Pole-based Localization",
   "type": "paper",
   "source": "[待核查] arXiv:2412.04334",
   "aliases": []
  },
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   "source": "https://arxiv.org/abs/2008.01760",
   "aliases": []
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   "source": "https://arxiv.org/abs/2406.03835",
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   "source": "https://arxiv.org/abs/2601.01000",
   "aliases": []
  },
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   "name": "SCORE Semantic Line Map Relocalization",
   "type": "paper",
   "source": "https://arxiv.org/abs/2503.03254",
   "aliases": []
  },
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   "source": "https://arxiv.org/abs/2005.04259",
   "aliases": [
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   ]
  },
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   "type": "framework",
   "source": "https://github.com/yuantianyuan01/StreamMapNet",
   "aliases": [
    "StreamMapNet",
    "Stream Map Net"
   ]
  },
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   "type": "dataset",
   "source": "https://argoverse.github.io/user-guide/getting_started.html",
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    "Argoverse 2",
    "av2"
   ]
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   "type": "paper",
   "source": "https://arxiv.org/abs/2307.14981",
   "aliases": [
    "MapNeRF",
    "Map NeRF"
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  },
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   "source": "https://dspace.mit.edu/handle/1721.1/138000.2",
   "aliases": [
    "Convex MPC Cheetah 3 Paper",
    "cMPC Paper",
    "Di Carlo IROS 2018"
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   "type": "tool",
   "source": "https://github.com/stack-of-tasks/pinocchio",
   "aliases": []
  },
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   "name": "Zhang 2018 Double-closed-loop ADRC",
   "type": "paper",
   "source": "https://doi.org/10.1016/j.ast.2018.06.017",
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    "Double-closed-loop ADRC",
    "Zhang 2018 Quadrotor ADRC"
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   "type": "paper",
   "source": "https://www.mdpi.com/2076-0825/15/6/286",
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    "LADRC Quadrotor",
    "Crazyflie ADRC"
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   "name": "ACDRC 2022 ISA Trans",
   "type": "paper",
   "source": "https://doi.org/10.1016/j.isatra.2022.01.012",
   "aliases": [
    "ACDRC",
    "Adaptive Composite Disturbance Rejection"
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  },
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   "name": "Araar Aouf 2014 LQ vs H-infinity",
   "type": "paper",
   "source": "https://doi.org/10.1109/CONTROL.2014.6915128",
   "aliases": [
    "LQ vs H-infinity",
    "Full Linear Control Quadrotor"
   ]
  },
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   "name": "Swift Autonomous Drone Racing 2023",
   "type": "paper",
   "source": "https://doi.org/10.1038/s41586-023-06419-4",
   "aliases": [
    "Swift",
    "自主竞速无人机"
   ]
  },
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   "type": "framework",
   "source": "https://github.com/zju3dv/rnin-vio",
   "aliases": [
    "RNIN-VIO",
    "神经惯性里程计"
   ]
  },
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   "name": "Kaufmann ICRA 2022 Benchmark",
   "type": "paper",
   "source": "https://arxiv.org/abs/2202.10796",
   "aliases": [
    "Kaufmann 2022",
    "RL Sim-to-Real Benchmark"
   ]
  },
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   "name": "VIO Yaw Observability Analysis",
   "type": "paper",
   "source": "https://wenku.csdn.net/answer/2vkw8m6w5z",
   "aliases": [
    "Yaw Observability",
    "VIO yaw drift"
   ]
  },
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   "name": "rqt_runtime_monitor",
   "type": "package",
   "source": "https://github.com/ros-visualization/rqt_runtime_monitor",
   "aliases": []
  },
  "AST_e137bbfd": {
   "name": "monit",
   "type": "tool",
   "source": "https://mmonit.com/monit/",
   "aliases": [
    "monit process monitor"
   ]
  },
  "AST_e5007e94": {
   "name": "Linux Kernel Watchdog Subsystem",
   "type": "framework",
   "source": "https://www.kernel.org/doc/html/latest/watchdog/watchdog-api.html",
   "aliases": [
    "watchdog subsystem",
    "Linux watchdog",
    "WDT kernel interface"
   ]
  },
  "AST_7a69ceb1": {
   "name": "greenboot-default-health-checks",
   "type": "package",
   "source": "https://docs.redhat.com/zh-cn/documentation/red_hat_build_of_microshift/4.17/html/running_applications/microshift-greenboot-included-health-checks",
   "aliases": []
  },
  "AST_2c127696": {
   "name": "gRPC",
   "type": "framework",
   "source": "https://github.com/grpc/grpc",
   "aliases": [
    "gRPC",
    "grpc",
    "google.golang.org/grpc"
   ]
  },
  "AST_b54bac68": {
   "name": "Netflix Eureka",
   "type": "framework",
   "source": "https://github.com/Netflix/eureka",
   "aliases": [
    "Netflix Eureka",
    "Spring Cloud Eureka"
   ]
  },
  "AST_4cded2c5": {
   "name": "bondcpp",
   "type": "ros_package",
   "source": "https://github.com/ros/bond_core",
   "aliases": [
    "bondcpp",
    "bond_core",
    "ROS2 bond"
   ]
  },
  "AST_76bad1d0": {
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  },
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   "source": "https://developer.hashicorp.com/vault/docs/concepts/policies",
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    "Vault ACL"
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    "MinIO Key Encryption Service"
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    "Intermediate-Representation Semantic Parsing"
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   "source": "[待核查]",
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   "source": "https://github.com/MagRobotics/MagRobot",
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    "MagRobot",
    "磁导航机器人仿真平台"
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   "source": "https://naviq.com/products/mts160-magnetic-line-sensor",
   "aliases": [
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    "Naviq MTS160"
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   "name": "Naviq EQSP32 IoT Controller",
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   "source": "https://naviq.com/products/eqsp32-iot-controller",
   "aliases": [
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    "Naviq EQSP32"
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   "source": "https://www.xjishu.com/zhuanli/52/202511063654.html",
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   "source": "https://www.xjishu.com/zhuanli/52/202511063654.html",
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   "source": "https://naviq.com/blog/articles/cost-optimized-magnetic-guided-agv-using-the-naviq-mts160-sensor-and-the-eqsp32-iot-controller",
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    "MTS160 marker"
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   "name": "Yangshan Port Phase IV Magnetic Nail System",
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   "source": "王跃全 2018《水运工程》洋山深水港全自动化码头 AGV 磁钉安装定位方法",
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  },
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   "aliases": [
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  },
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   "source": "https://arxiv.org/abs/2310.12345",
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   "type": "tool",
   "source": "https://github.com/JuliaPOMDP/BasicPOMCP.jl",
   "aliases": [
    "BasicPOMCP"
   ]
  },
  "AST_80101b7b": {
   "name": "POMCPOW.jl",
   "type": "tool",
   "source": "https://github.com/JuliaPOMDP/POMCPOW.jl",
   "aliases": [
    "POMCPOW"
   ]
  },
  "AST_e0b8f652": {
   "name": "ParticleFilters.jl",
   "type": "tool",
   "source": "https://github.com/JuliaPOMDP/ParticleFilters.jl",
   "aliases": [
    "ParticleFilters"
   ]
  },
  "AST_6162c778": {
   "name": "adaptive-pomcp",
   "type": "tool",
   "source": "https://github.com/zkytony/adaptive-pomcp",
   "aliases": [
    "adaptive-pomcp"
   ]
  },
  "AST_996e6280": {
   "name": "Online Planning for Interactive Robotics under Uncertainty",
   "type": "paper",
   "source": "https://arxiv.org/abs/2001.XXXX",
   "aliases": [
    "TAPIR"
   ]
  },
  "AST_4cbdfff0": {
   "name": "isaac_ros_dope",
   "type": "ros_package",
   "source": "https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_pose_estimation",
   "aliases": [
    "Isaac ROS DOPE",
    "nvidia isaac ros dope",
    "isaac_ros_dope",
    "Isaac ROS DNN pose",
    "isaac_ros_pose_estimation"
   ]
  },
  "AST_c7e47a81": {
   "name": "isaac_ros_foundationpose",
   "type": "ros_package",
   "source": "https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_pose_estimation",
   "aliases": [
    "Isaac ROS FoundationPose",
    "isaac_ros_foundationpose",
    "NVIDIA FoundationPose ROS2"
   ]
  },
  "AST_b0f5898e": {
   "name": "EasyMocap (Multi-View Markerless Motion Capture)",
   "type": "framework",
   "source": "https://github.com/zju3dv/EasyMocap",
   "aliases": [
    "EasyMocap",
    "ZJU MoCap Toolkit",
    "zju3dv EasyMocap"
   ]
  },
  "AST_31fbc138": {
   "name": "pytorch-grad-cam",
   "type": "package",
   "source": "https://github.com/jacobgil/pytorch-grad-cam",
   "aliases": [
    "grad-cam",
    "pytorch-gradcam",
    "Jacob Gildenblat CAM library"
   ]
  },
  "AST_1350d701": {
   "name": "ProtoX",
   "type": "model",
   "source": "[待核查] https://openreview.net/forum?id=nyBJcnhjAoy",
   "aliases": [
    "Prototype-based Policy Explanation",
    "Prototypical State Explanation"
   ]
  },
  "AST_e6a24651": {
   "name": "STLCG",
   "type": "package",
   "source": "https://github.com/StanfordASL/stlcg",
   "aliases": [
    "Signal Temporal Logic Computational Graphs",
    "STL robustness PyTorch",
    "StanfordASL/stlcg"
   ]
  },
  "AST_c17d2709": {
   "name": "CalibTIP (AdaRound)",
   "type": "package",
   "source": "https://github.com/itayhubara/CalibTIP",
   "aliases": [
    "AdaRound",
    "itayhubara/CalibTIP",
    "Adaptive Rounding PTQ"
   ]
  },
  "AST_6d890fb3": {
   "name": "BRECQ",
   "type": "package",
   "source": "https://github.com/yhhhli/BRECQ",
   "aliases": [
    "yhhhli/BRECQ",
    "Block Reconstruction PTQ"
   ]
  },
  "AST_07f77b3c": {
   "name": "AutoGPTQ",
   "type": "package",
   "source": "https://github.com/AutoGPTQ/AutoGPTQ",
   "aliases": [
    "PanQiWei/AutoGPTQ",
    "GPTQModel (successor)"
   ]
  },
  "AST_b797e265": {
   "name": "SmoothQuant",
   "type": "package",
   "source": "https://github.com/mit-han-lab/smoothquant",
   "aliases": [
    "mit-han-lab/smoothquant",
    "Channel-wise Smooth Quantization"
   ]
  },
  "AST_d0c2b6c5": {
   "name": "llamafile",
   "type": "package",
   "source": "https://github.com/mozilla-ai/llamafile",
   "aliases": [
    "mozilla-ai/llamafile",
    "Mozilla-Ocho/llamafile (old URL)",
    "Cosmopolitan LLM",
    "llamafile"
   ]
  },
  "AST_d2b13d25": {
   "name": "LM Studio",
   "type": "framework",
   "source": "https://github.com/lmstudio-ai/lmstudio.js",
   "aliases": [
    "lmstudio-ai",
    "LM Studio Desktop",
    "LM Studio SDK"
   ]
  },
  "AST_fb1b55b0": {
   "name": "convert_hf_to_gguf.py",
   "type": "package",
   "source": "https://github.com/ggml-org/llama.cpp/blob/master/convert_hf_to_gguf.py",
   "aliases": [
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    "convert.py (deprecated)"
   ]
  },
  "AST_ab7da3ed": {
   "name": "MATLAB controllerAPF",
   "type": "tool",
   "source": "https://www.mathworks.com/help/robotics/ref/controllerapf.html",
   "aliases": [
    "MATLAB APF controller",
    "Robotics System Toolbox APF"
   ]
  },
  "AST_d32d9862": {
   "name": "Kim-Khosla 1992 Panel Method Formulas",
   "type": "tool",
   "source": "https://doi.org/10.1109/70.143352",
   "aliases": [
    "Kim-Khosla panel method",
    "HPF panel method source",
    "harmonic potential panel formula",
    "Kim-Khosla 1992 Panel Method 公式"
   ]
  },
  "AST_23714dd5": {
   "name": "nav2_navfn_planner (ROS2)",
   "type": "ros_package",
   "source": "https://github.com/ros-navigation/navigation2/tree/main/nav2_navfn_planner",
   "aliases": [
    "Nav2 NavFn planner",
    "NavFn planner plugin",
    "GridBased planner Nav2",
    "ROS2 nav2_navfn_planner"
   ]
  },
  "AST_91346d27": {
   "name": "Kim-Kim-Kim-Lim 2024 APF+WF Multi-Robot Navigation",
   "type": "tool",
   "source": "https://arxiv.org/abs/2409.10332",
   "aliases": [
    "APF-WF multi-robot",
    "hybrid APF wall follower",
    "RS/LS APF switching"
   ]
  },
  "AST_6091f2b8": {
   "name": "RuslanAgishev motion_planning",
   "type": "package",
   "source": "https://github.com/RuslanAgishev/motion_planning",
   "aliases": [
    "RRT-APF layered planner",
    "motion_planning RRT gradient"
   ]
  },
  "AST_0a6f2565": {
   "name": "PourIt",
   "type": "framework",
   "source": "https://github.com/hetolin/PourIt",
   "aliases": [
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    "hetolin/PourIt"
   ]
  },
  "AST_d72e6fee": {
   "name": "SAR-Net",
   "type": "framework",
   "source": "https://github.com/hetolin/SAR-Net",
   "aliases": [
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   ]
  },
  "AST_7d3df13a": {
   "name": "PourIt Dataset",
   "type": "dataset",
   "source": "https://drive.google.com/file/d/1X_IyPt9N9-AtqVwHWrL5nVqIuNMileTY/view",
   "aliases": [
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   ]
  },
  "AST_7c7c07a7": {
   "name": "UW Liquid Pouring Dataset",
   "type": "dataset",
   "source": "https://rse-lab.cs.washington.edu/lpd/",
   "aliases": [
    "University of Washington Liquid Pouring Dataset",
    "Schenck Fox LPD"
   ]
  },
  "AST_f5cdf732": {
   "name": "Transparent Liquid Pouring (Narasimhan et al.)",
   "type": "tool",
   "source": "https://sites.google.com/view/transparentliquidpouring",
   "aliases": [
    "Self-supervised Transparent Liquid Segmentation",
    "CMU Transparent Pouring"
   ]
  },
  "AST_1e0f99cd": {
   "name": "Robot Motion Planning for Pouring Liquids (ICAPS 2016)",
   "type": "paper",
   "source": "https://aaai.org/papers/00518-robot-motion-planning-for-pouring-liquids/",
   "aliases": [
    "Pan et al. Pouring Planning ICAPS16"
   ]
  },
  "AST_a3ed50ef": {
   "name": "Kinematic Controller for Liquid Pouring with SPH (Appl. Sci. 2019)",
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   "source": "https://mdpi.com/2076-3417/9/23/5007",
   "aliases": [
    "Camporredondo SPH Pouring 2019",
    "SIM Pouring Controller"
   ]
  },
  "AST_0317c635": {
   "name": "LabLiquidVision",
   "type": "tool",
   "source": "https://github.com/DaniSchober/LabLiquidVision",
   "aliases": [
    "Schober LabLiquidVision",
    "DTU Laboratory Pouring"
   ]
  },
  "AST_4ab9d8fb": {
   "name": "TCN (Time-Contrastive Networks)",
   "type": "framework",
   "source": "https://github.com/tensorflow/models/tree/master/research/tcn",
   "aliases": [
    "tensorflow/tcn",
    "Time-Contrastive Networks reference implementation"
   ]
  },
  "AST_7f912312": {
   "name": "ARCADE",
   "type": "tool",
   "source": "https://yy-gx.github.io/ARCADE/",
   "aliases": [
    "AR Demonstration Collection",
    "yy-gx/ARCADE"
   ]
  },
  "AST_d6f281d3": {
   "name": "Robot Gaining Accurate Pouring Skills through Self-Supervised Learning and Generalization (RAS 2021)",
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   "source": "https://www.sciencedirect.com/science/article/pii/S0921889020305533",
   "aliases": [
    "Huang et al. Self-Supervised Pouring RAS21"
   ]
  },
  "AST_f2620c80": {
   "name": "GMM Enabled by MMFNet (IEEE TNNLS 2025)",
   "type": "paper",
   "source": "https://pubmed.ncbi.nlm.nih.gov/39437288/",
   "aliases": [
    "Wang MMFNet TNNLS25",
    "MMFNet Pouring"
   ]
  },
  "AST_277f1b75": {
   "name": "Explainable Hierarchical Imitation Learning for Robotic Drink Pouring (TASE 2022)",
   "type": "paper",
   "source": "https://pub.uni-bielefeld.de/person/15278595",
   "aliases": [
    "Zhang HIL Pouring TASE22"
   ]
  },
  "AST_48c3d6f2": {
   "name": "Pouring by Feel: Tactile and Proprioceptive Sensing for Accurate Pouring (ICRA 2022)",
   "type": "paper",
   "source": "https://arxiv.org/abs/2310.18473",
   "aliases": [
    "Piacenza Pouring by Feel ICRA22"
   ]
  },
  "AST_ec96826b": {
   "name": "Look and Listen: Multi-Sensory Pouring Network and Dataset (ICRA 2022)",
   "type": "paper",
   "source": "https://ieeexplore.ieee.org/document/9812125",
   "aliases": [
    "Burns Look and Listen ICRA22"
   ]
  },
  "AST_20c47025": {
   "name": "DLR SARA Pour Dataset (RLDS)",
   "type": "dataset",
   "source": "https://www.tensorflow.org/datasets/catalog/dlr_sara_pour_converted_externally_to_rlds",
   "aliases": [
    "dlr_sara_pour_rlds",
    "DLR SARA Pour RLDS"
   ]
  },
  "AST_ed7be36c": {
   "name": "Learning to Pour using Deep Deterministic Policy Gradients (IROS 2018)",
   "type": "paper",
   "source": "[待核查]",
   "aliases": [
    "Do DDPG Pouring IROS18"
   ]
  },
  "AST_e17b4e5f": {
   "name": "Guiding Reinforcement Learning with Shared Control Templates (ICRA 2023)",
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   "source": "https://elib.dlr.de/193739/1/padalkar2023rlsct.pdf",
   "aliases": [
    "Padalkar SCT RL ICRA23"
   ]
  },
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   "name": "OnRobot Screwdriver",
   "type": "tool",
   "source": "https://onrobot.com/en/products/onrobot-screwdriver",
   "aliases": [
    "OnRobot Screw Driver",
    "OnRobot Screwdriving End Effector"
   ]
  },
  "AST_c67a59a7": {
   "name": "Robotiq Screwdriving Solution SD-100",
   "type": "tool",
   "source": "https://robotiq.com/solutions/screwdriving",
   "aliases": [
    "Robotiq SD-100",
    "Robotiq Screwdriver",
    "Robotiq Screwdriving Kit"
   ]
  },
  "AST_1b9c5d33": {
   "name": "AURSAD Dataset",
   "type": "dataset",
   "source": "https://arxiv.org/abs/2102.01409",
   "aliases": [
    "AURSAD",
    "Universal Robot Screwdriving Anomaly Dataset"
   ]
  },
  "AST_4f02ec57": {
   "name": "Broetje MFEE Multi Function End Effector",
   "type": "tool",
   "source": "https://www.broetje-automation.de/en/",
   "aliases": [
    "MFEE",
    "Multi Function End Effector",
    "Broetje Drilling End Effector"
   ]
  },
  "AST_0766236c": {
   "name": "MICRON Micron-Aware Hand-Held Surgical Drill",
   "type": "tool",
   "source": "https://jhu-lcsr.github.io/micron/",
   "aliases": [
    "MICRON",
    "Micron-Aware Drill",
    "JHU Micron",
    "Active Tremor Compensation Drill"
   ]
  },
  "AST_298d7ed1": {
   "name": "FeralInteractive GameMode",
   "type": "tool",
   "source": "https://github.com/FeralInteractive/gamemode",
   "aliases": [
    "gamemoded",
    "Feral GameMode",
    "libgamemodeauto",
    "gamemoderun"
   ]
  },
  "AST_34d7eb97": {
   "name": "Pisa/IIT SoftHand",
   "type": "robot",
   "source": "https://www.naturalmachinemotioninitiative.com/softeurope",
   "aliases": [
    "SoftHand",
    "Pisa SoftHand",
    "IIT SoftHand",
    "qbsofthand"
   ]
  },
  "AST_e0e1d988": {
   "name": "BarrettHand",
   "type": "robot",
   "source": "https://barrett.com/robot/products/hand",
   "aliases": [
    "Barrett Hand BH8",
    "BH8-280",
    "WAM hand"
   ]
  },
  "AST_d04c55d7": {
   "name": "Velvet Fingers",
   "type": "robot",
   "source": "https://ieeexplore.ieee.org/document/6907044",
   "aliases": [
    "velvet fingers gripper",
    "active surface gripper",
    "Krug Velvet Fingers"
   ]
  },
  "AST_d28d4fbe": {
   "name": "SINAMICS S120",
   "type": "framework",
   "source": "https://www.siemens.com/global/en/products/drives/sinamics/low-voltage-converters/servo-converter/sinamics-s120.html",
   "aliases": [
    "SINAMICS S120 Booksize",
    "SINAMICS S120 Chassis",
    "Siemens S120",
    "6SL33xx"
   ]
  },
  "AST_258928e7": {
   "name": "SOMANET SMM (Safe Motion Module)",
   "type": "framework",
   "source": "https://www.synapticon.com/zh/motion-control-academy/sichere-stopp-funktionen-ss1-ss2-sos",
   "aliases": [
    "Synapticon Safe Motion Module",
    "SOMANET Safety",
    "Circulo Safe Motion",
    "SOMANET SMM"
   ]
  },
  "AST_2fea4d74": {
   "name": "Novosense SafeNovo (ISO 26262 Isolated Gate Driver)",
   "type": "tool",
   "source": "https://www.novosns.com",
   "aliases": [
    "Novosense Isolated Gate Driver",
    "NSi68xx SafeNovo",
    "NSD26xx Series",
    "纳芯微隔离栅极驱动"
   ]
  },
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   "name": "Panasonic MINAS A6S",
   "type": "framework",
   "source": "https://device.panasonic.cn/ac/c/motor/fa-motor/ac-servo/a6s/index.jsp",
   "aliases": [
    "Panasonic MINAS A6 Family",
    "松下A6伺服",
    "MINAS A6SG",
    "MINAS A6SE",
    "MINAS A6SF"
   ]
  },
  "AST_bfeb0964": {
   "name": "PX4 Battery Failsafe (Open Source Flight Stack)",
   "type": "framework",
   "source": "https://docs.px4.io/v1.15/en/config/safety.html#battery-failsafe",
   "aliases": [
    "PX4 Low Battery Failsafe",
    "PX4 Power Safety",
    "PX4 RTL/Land/Terminate"
   ]
  },
  "AST_e90e4207": {
   "name": "ArduPilot Battery Failsafe (Open Source Flight Stack)",
   "type": "framework",
   "source": "https://ardupilot.org/copter/docs/failsafe-battery.html",
   "aliases": [
    "ArduPilot Low Battery Failsafe",
    "ArduCopter Battery Failsafe",
    "ArduPilot SmartRTL"
   ]
  },
  "AST_8411ee6e": {
   "name": "Siemens SITOP DC UPS (Industrial DC UPS Module)",
   "type": "framework",
   "source": "http://www.ad.siemens.com.cn/download/documentdetail_6454.html",
   "aliases": [
    "SITOP UPS",
    "Siemens Industrial UPS",
    "SITOP UPS1100",
    "SITOP UPS5000"
   ]
  },
  "AST_8db3f939": {
   "name": "Nabot C1103 Controller Built-in UPS (Supercapacitor Module)",
   "type": "framework",
   "source": "https://www.inexbot.com/zh/product/content/t53jp6od0gwiq7uv7m8p94fg",
   "aliases": [
    "纳博特C1103",
    "Nabot UPS Controller",
    "INEXBOT C1103"
   ]
  },
  "AST_915e52fa": {
   "name": "TI TPS212x/TPS2594 eFuse and Power MUX",
   "type": "tool",
   "source": "https://www.ti.com/product/TPS2121",
   "aliases": [
    "TI Power MUX",
    "TI eFuse",
    "TPS2120",
    "TPS2121",
    "TPS2594",
    "Ideal Diode ORing"
   ]
  },
  "AST_e96371ae": {
   "name": "Everspin MRAM (Magnetoresistive RAM)",
   "type": "tool",
   "source": "https://www.everspin.com",
   "aliases": [
    "Everspin MRAM",
    "MR25H256",
    "Magnetoresistive RAM",
    "Non-volatile RAM"
   ]
  },
  "AST_cde0f603": {
   "name": "CoorGrasp",
   "type": "framework",
   "source": "https://github.com/ada-grasp-ctrl/ada-grasp-ctrl",
   "aliases": [
    "ada-grasp-ctrl",
    "Coordinated Contact Control",
    "CoorGrasp MPC"
   ]
  },
  "AST_4e81cf22": {
   "name": "DexHand-021",
   "type": "robot",
   "source": "https://www.dex-robot.com/en/productionDexhand",
   "aliases": [
    "DexHand 021",
    "Dex-Robots Dexterous Hand",
    "因时五指灵巧手"
   ]
  },
  "AST_ddc42311": {
   "name": "ImplicitRDP",
   "type": "framework",
   "source": "https://github.com/Chen-Wendi/ImplicitRDP",
   "aliases": [
    "End-to-End Visual-Force Diffusion Policy",
    "Implicit RDP",
    "Structural Slow-Fast Learning"
   ]
  },
  "AST_f1ea6ef5": {
   "name": "Autoware Obstacle Velocity Limiter",
   "type": "ros_package",
   "source": "https://github.com/autowarefoundation/autoware.universe/tree/main/planning/motion_velocity_planner/autoware_motion_velocity_obstacle_velocity_limiter_module",
   "aliases": [
    "obstacle_velocity_limiter",
    "Autoware OVL",
    "autoware_motion_velocity_obstacle_velocity_limiter_module"
   ]
  },
  "AST_49f7db42": {
   "name": "Universal Robots Scaled Controllers",
   "type": "ros_package",
   "source": "https://github.com/UniversalRobots/Universal_Robots_ROS_scaled_controllers",
   "aliases": [
    "ur_scaled_controllers",
    "scaled_joint_trajectory_controller",
    "speed_scaling_interface",
    "UR speed scaling"
   ]
  },
  "AST_33f93620": {
   "name": "C²U-MPPI: Chance-Constrained Unscented MPPI",
   "type": "paper",
   "source": "https://doi.org/10.1109/LRA.2025.3540477",
   "aliases": [
    "C2U-MPPI",
    "CC-U-MPPI",
    "Mohamed-Ali-Liu 2025",
    "Chance-Constrained Unscented MPPI"
   ]
  },
  "AST_7479ed6b": {
   "name": "SVSDF: Implicit Swept Volume SDF for Continuous Collision Avoidance",
   "type": "paper",
   "source": "https://doi.org/10.1145/3658181",
   "aliases": [
    "SVSDF",
    "Implicit Swept Volume",
    "Wang-Zhang-Xu-Gao 2024",
    "SVSDF-CCA"
   ]
  },
  "AST_ef2ec29c": {
   "name": "CSSDF-Net: Configuration-Space SDF Network (SJTU 2026)",
   "type": "paper",
   "source": "https://arxiv.org/abs/2601.02658",
   "aliases": [
    "CSSDF-Net",
    "Configuration-Space SDF",
    "C-space SDF Network"
   ]
  },
  "AST_4efe32b2": {
   "name": "Vision Foundation Model TTC: Zero-Shot Time-to-Collision from RGB (arXiv 2026)",
   "type": "paper",
   "source": "https://arxiv.org/abs/2607.07885",
   "aliases": [
    "Vision TTC 2026",
    "Foundation Model TTC",
    "Zero-shot TTC"
   ]
  },
  "AST_34cbb610": {
   "name": "Digital-Twin-Fault-Diagnosis (DANN)",
   "type": "framework",
   "source": "https://github.com/JialingRichard/Digital-Twin-Fault-Diagnosis",
   "aliases": [
    "JialingRichard/Digital-Twin-Fault-Diagnosis",
    "DANN-DT Fault Diagnosis",
    "DT-Fault-Diagnosis"
   ]
  },
  "AST_6ffd3cea": {
   "name": "roboterax/video-prediction-policy",
   "type": "tool",
   "source": "https://github.com/roboterax/video-prediction-policy",
   "aliases": [
    "VPP",
    "video-prediction-policy"
   ]
  },
  "AST_a32ed928": {
   "name": "edenton/svg",
   "type": "tool",
   "source": "https://github.com/edenton/svg",
   "aliases": [
    "SVG-LP",
    "SVG-FP",
    "Stochastic Video Generation"
   ]
  },
  "AST_64fec975": {
   "name": "tensorflow/models/research/video_prediction",
   "type": "tool",
   "source": "https://github.com/tensorflow/models/tree/master/research/video_prediction",
   "aliases": [
    "tensorflow models video prediction",
    "CDNA official TF implementation"
   ]
  },
  "AST_8ac5a3e2": {
   "name": "I-JEPA Image Joint-Embedding Predictive Architecture",
   "type": "framework",
   "source": "https://github.com/facebookresearch/ijepa",
   "aliases": [
    "facebookresearch/ijepa",
    "Image-based Joint-Embedding Predictive Architecture",
    "I-JEPA CVPR 2023"
   ]
  },
  "AST_6503c058": {
   "name": "TacFiLM",
   "type": "model",
   "source": "https://arxiv.org/abs/2603.14604",
   "aliases": [
    "Tactile Modality Fusion for VLA",
    "TacFiLM"
   ]
  },
  "AST_43f4dc74": {
   "name": "FELT (Feature-Extracted Latent Tactile)",
   "type": "model",
   "source": "https://felt-tactile.github.io/",
   "aliases": [
    "FELT visuo-tactile",
    "Feature-Extracted Latent Tactile",
    "zinanli/FELT (待确认)"
   ]
  },
  "AST_941a89a8": {
   "name": "TacImag Tactile Imagination Framework",
   "type": "model",
   "source": "https://tacimag.github.io/",
   "aliases": [
    "TacImag",
    "Tactile Imagination",
    "ZhiyuanZhang-TacImag (待确认)"
   ]
  },
  "AST_13141532": {
   "name": "Kepler-Encoder-v0.1 Multimodal Robot Encoder",
   "type": "model",
   "source": "https://arxiv.org/abs/2607.13522",
   "aliases": [
    "Kepler-Encoder",
    "Menlo Robot Multimodal Encoder"
   ]
  },
  "AST_9c15be51": {
   "name": "ferroplan",
   "type": "framework",
   "source": "https://github.com/hhh42/ferroplan",
   "aliases": [
    "ferroplan PDDL planner",
    "Rust PDDL3 planner",
    "ff planner Rust"
   ]
  },
  "AST_cd8b53f5": {
   "name": "SGPlan5",
   "type": "framework",
   "source": "[待核查]",
   "aliases": [
    "SGPlan PDDL3",
    "SGPlan preference planner"
   ]
  },
  "AST_3b38917b": {
   "name": "jsk_planning",
   "type": "ros_package",
   "source": "https://github.com/jsk-ros-pkg/jsk_planning",
   "aliases": [
    "JSK PDDL planner ROS",
    "jsk_ros_pddl"
   ]
  },
  "AST_718c4dcd": {
   "name": "LCBS",
   "type": "framework",
   "source": "https://github.com/Intelligent-Reliable-Autonomous-Systems/LCBS",
   "aliases": [
    "LCBS planner",
    "lexicographic MAPF solver",
    "MO-MAPF lexicographic",
    "LCBS C++ MAPF"
   ]
  },
  "AST_1b1d3f36": {
   "name": "ReCouPLe",
   "type": "framework",
   "source": "https://github.com/mj-hwang/ReCouPLe",
   "aliases": [
    "causally robust PbRL",
    "rationale-augmented reward learning",
    "ReCouPLe ICLR2026"
   ]
  },
  "AST_c0f8da29": {
   "name": "asprin",
   "type": "package",
   "source": "https://github.com/potassco/asprin",
   "aliases": [
    "asprin ASP preference framework",
    "potassco asprin",
    "ASP cp-nets solver"
   ]
  },
  "AST_645bb8a7": {
   "name": "tuw_multi_robot_ctrl",
   "type": "ros_package",
   "source": "https://github.com/tuw-robotics/tuw_multi_robot",
   "aliases": [
    "tuw_controller",
    "MultiRobotController"
   ]
  },
  "AST_f9867628": {
   "name": "tuw_multi_robot_demo",
   "type": "ros_package",
   "source": "https://github.com/tuw-robotics/tuw_multi_robot",
   "aliases": []
  },
  "AST_cb33aa50": {
   "name": "PIBT2",
   "type": "framework",
   "source": "https://github.com/Kei18/pibt2",
   "aliases": [
    "pibt2",
    "PIBT reference implementation",
    "Okumura PIBT"
   ]
  },
  "AST_f8ca91aa": {
   "name": "Priority Graph Coordination Framework (Gregoire et al.)",
   "type": "framework",
   "source": "https://arxiv.org/abs/1306.0785 ; https://arxiv.org/abs/1310.5828",
   "aliases": [
    "Gregoire Priority Graph",
    "Priority Homotopy Coordination",
    "MINES ParisTech Priority Control"
   ]
  },
  "AST_77f11ad9": {
   "name": "MD-PIBT",
   "type": "tool",
   "source": "https://github.com/lunjohnzhang/MD-PIBT",
   "aliases": [
    "MD-PIBT",
    "Multi-Dependency PIBT",
    "Agent Dependency Graph PIBT"
   ]
  },
  "AST_20a4c402": {
   "name": "Percepio Tracealyzer",
   "type": "tool",
   "source": "https://percepio.com/tracealyzer/",
   "aliases": [
    "Tracealyzer",
    "Percepio Trace Recorder",
    "FreeRTOS+Trace"
   ]
  },
  "AST_26686d5f": {
   "name": "SEGGER SystemView",
   "type": "tool",
   "source": "https://www.segger.com/products/development-tools/systemview/",
   "aliases": [
    "SystemView",
    "SEGGER SystemView"
   ]
  },
  "AST_4b064f31": {
   "name": "Trampoline RTOS",
   "type": "framework",
   "source": "https://github.com/TrampolineRTOS/trampoline",
   "aliases": [
    "Trampoline",
    "TrampolineRTOS",
    "open AUTOSAR OS",
    "OSEK open source"
   ]
  },
  "AST_c06f55d5": {
   "name": "Erika Enterprise v3 (ERIKA3)",
   "type": "framework",
   "source": "https://github.com/evidence/erika3",
   "aliases": [
    "ERIKA3",
    "Erika Enterprise",
    "Evidence RTOS",
    "RT-Druid"
   ]
  },
  "AST_bd7b3bd2": {
   "name": "glibc NPTL (PTHREAD_PRIO_PROTECT)",
   "type": "framework",
   "source": "https://sourceware.org/git/glibc.git",
   "aliases": [
    "glibc PTHREAD_PRIO_PROTECT",
    "NPTL ceiling mutex",
    "POSIX protect protocol"
   ]
  },
  "AST_f7ed98e8": {
   "name": "GNAT Runtime (Ada Ceiling_Locking)",
   "type": "framework",
   "source": "https://gcc.gnu.org/git/gcc.git",
   "aliases": [
    "GNAT",
    "Ada runtime",
    "GNAT libgnarl",
    "AdaCore runtime"
   ]
  },
  "AST_319e3206": {
   "name": "μC/OS-II / μC/OS-III",
   "type": "framework",
   "source": "https://github.com/SiliconLabs/uC-OS2",
   "aliases": [
    "uC-OS",
    "uCOS-II",
    "Micrium",
    "Silicon Labs uC/OS"
   ]
  },
  "AST_576486ff": {
   "name": "Zephyr RTOS (CONFIG_PRIORITY_CEILING)",
   "type": "framework",
   "source": "https://github.com/zephyrproject-rtos/zephyr",
   "aliases": [
    "Zephyr ceiling mutex",
    "k_mutex prio_ceiling",
    "Zephyr PCP"
   ]
  },
  "AST_1d4af299": {
   "name": "FreeRTOS Critical Section Primitives",
   "type": "framework",
   "source": "https://github.com/FreeRTOS/FreeRTOS-Kernel",
   "aliases": [
    "FreeRTOS critical section",
    "vPortEnterCritical",
    "BASEPRI critical",
    "taskENTER_CRITICAL"
   ]
  },
  "AST_5147849f": {
   "name": "DPDK rte_ring",
   "type": "framework",
   "source": "https://github.com/DPDK/dpdk",
   "aliases": [
    "DPDK ring",
    "rte_ring",
    "DPDK lockless queue"
   ]
  },
  "AST_467c34ea": {
   "name": "FreeRTOS StreamBuffer / MessageBuffer",
   "type": "framework",
   "source": "https://github.com/FreeRTOS/FreeRTOS-Kernel",
   "aliases": [
    "FreeRTOS StreamBuffer",
    "FreeRTOS MessageBuffer",
    "xStreamBufferSend"
   ]
  },
  "AST_df52ef4f": {
   "name": "glibc NPTL Robust Mutex",
   "type": "framework",
   "source": "https://sourceware.org/git/glibc.git",
   "aliases": [
    "glibc robust mutex",
    "NPTL PTHREAD_MUTEX_ROBUST",
    "FUTEX_ROBUST",
    "EOWNERDEAD"
   ]
  },
  "AST_f6bb5329": {
   "name": "Linux Kernel kfifo",
   "type": "framework",
   "source": "https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git",
   "aliases": [
    "Linux kfifo",
    "kernel FIFO",
    "kfifo ring buffer"
   ]
  },
  "AST_d6f4d783": {
   "name": "VxWorks 653 (ARINC 653 Partitioning)",
   "type": "framework",
   "source": "https://www.windriver.com/products/vxworks/",
   "aliases": [
    "VxWorks 653",
    "ARINC 653 RTOS",
    "Wind River VxWorks 653",
    "IMA partition OS"
   ]
  },
  "AST_cf019f0a": {
   "name": "VxWorks",
   "type": "framework",
   "source": "https://www.vxworks.net/",
   "aliases": [
    "VxWorks RTOS",
    "Wind River VxWorks"
   ]
  },
  "AST_240a9f33": {
   "name": "POK",
   "type": "framework",
   "source": "https://github.com/pok-kernel/pok",
   "aliases": [
    "POK kernel",
    "POK-ARINC653",
    "pok-kernel"
   ]
  },
  "AST_cd3d6292": {
   "name": "a653lib",
   "type": "tool",
   "source": "https://github.com/airbus/a653lib",
   "aliases": [
    "liba653",
    "Airbus a653lib",
    "ARINC 653 Linux emulation"
   ]
  },
  "AST_4de30356": {
   "name": "ScenicRules",
   "type": "framework",
   "source": "https://github.com/BerkeleyLearnVerify/ScenicRules",
   "aliases": [
    "Hierarchical Rulebook",
    "Wongpiromsarn Rulebook",
    "Rulebook Framework"
   ]
  },
  "AST_e969abce": {
   "name": "RAFL",
   "type": "framework",
   "source": "https://github.com/generalroboticslab/RAFL",
   "aliases": [
    "Residual Acceleration Field Learning",
    "RAFL Sim-to-Real",
    "generalroboticslab/RAFL"
   ]
  },
  "AST_8536272f": {
   "name": "DiffPD",
   "type": "simulator",
   "source": "https://github.com/mit-gfx/diff_pd",
   "aliases": [
    "Differentiable Projective Dynamics",
    "DiffPD Simulator",
    "mit-gfx/diff_pd"
   ]
  },
  "AST_2f445f27": {
   "name": "phMARL",
   "type": "framework",
   "source": "https://github.com/EduardoSebastianRodriguez/phMARL",
   "aliases": [
    "pH-MARL",
    "Physics-Informed MARL",
    "Port-Hamiltonian MARL",
    "EduardoSebastianRodriguez/phMARL"
   ]
  },
  "AST_92fac98e": {
   "name": "CNIL PIA",
   "type": "tool",
   "source": "https://github.com/LINCnil/pia",
   "aliases": [
    "PIA Software",
    "CNIL DPIA Tool",
    "LINCnil/pia"
   ]
  },
  "AST_a5a90098": {
   "name": "HoundDog.ai",
   "type": "tool",
   "source": "https://github.com/HoundDogAI/HoundDog",
   "aliases": [
    "HoundDog",
    "Privacy Code Scanner",
    "hounddogai"
   ]
  },
  "AST_3b8c2c0a": {
   "name": "IBM AI Privacy Toolkit",
   "type": "package",
   "source": "https://github.com/IBM/ai-privacy-toolkit",
   "aliases": [
    "ai-privacy-toolkit",
    "apt",
    "IBM APT",
    "SOFTX-D-22-00422"
   ]
  },
  "AST_98fe3f7f": {
   "name": "FATE",
   "type": "framework",
   "source": "https://github.com/FederatedAI/FATE",
   "aliases": [
    "FederatedAI/FATE",
    "FATE框架",
    "微众FATE"
   ]
  },
  "AST_1170f8c0": {
   "name": "CrypTen",
   "type": "framework",
   "source": "https://github.com/facebookresearch/CrypTen",
   "aliases": [
    "facebookresearch/CrypTen",
    "CrypTen MPC",
    "Meta CrypTen"
   ]
  },
  "AST_6ae5ac41": {
   "name": "SELinux Userspace Tools (policycoreutils)",
   "type": "tool",
   "source": "https://github.com/SELinuxProject/selinux",
   "aliases": [
    "SELinux userland",
    "policycoreutils",
    "audit2allow",
    "semodule",
    "SELinuxProject/selinux"
   ]
  },
  "AST_b90f5362": {
   "name": "AppArmor Userspace Tools (apparmor-utils)",
   "type": "tool",
   "source": "https://gitlab.com/apparmor/apparmor",
   "aliases": [
    "AppArmor userspace",
    "apparmor_parser",
    "aa-genprof",
    "aa-logprof"
   ]
  },
  "AST_729209a9": {
   "name": "libcap (Linux Capabilities Library)",
   "type": "package",
   "source": "https://git.kernel.org/pub/scm/libs/libcap/libcap.git",
   "aliases": [
    "libcap2",
    "Linux capabilities library",
    "setcap",
    "getcap",
    "capsh"
   ]
  },
  "AST_45c3b8d7": {
   "name": "libseccomp",
   "type": "package",
   "source": "https://github.com/seccomp/libseccomp",
   "aliases": [
    "libseccomp2",
    "seccomp library",
    "seccomp-bpf userspace"
   ]
  },
  "AST_05195a7c": {
   "name": "PROFIsafe Safety Communication Protocol",
   "type": "framework",
   "source": "https://www.profibus.com/technology/profisafe/",
   "aliases": [
    "PROFIsafe over PROFINET",
    "PROFIBUS Safety",
    "F-Host/F-Device Protocol",
    "IEC 61784-3-3"
   ]
  },
  "AST_f096b139": {
   "name": "CIP Safety (Common Industrial Protocol Safety)",
   "type": "framework",
   "source": "https://www.odva.org/Technology-Standards/Network-Technologies/CIP-Safety/",
   "aliases": [
    "CIP Safety over EtherNet/IP",
    "EtherNet/IP Safety",
    "ODVA CIP Safety"
   ]
  },
  "AST_e9aed8e7": {
   "name": "Falco (Cloud Native Runtime Security)",
   "type": "framework",
   "source": "https://github.com/falcosecurity/falco",
   "aliases": [
    "Falco Runtime Security",
    "Sysdig Falco",
    "CNCF Falco",
    "Cloud Native Runtime Detection",
    "Falco Threat Detection"
   ]
  },
  "AST_5f1ff995": {
   "name": "Cilium Tetragon (eBPF-based Runtime Security Enforcement)",
   "type": "framework",
   "source": "https://github.com/cilium/tetragon",
   "aliases": [
    "Cilium Tetragon",
    "eBPF Enforcement",
    "Tetragon Security",
    "Cilium Runtime Security",
    "BPF Enforcement Policy"
   ]
  },
  "AST_6a11a088": {
   "name": "Falcosidekick (Falco Event Forwarding and Response)",
   "type": "framework",
   "source": "https://github.com/falcosecurity/falcosidekick",
   "aliases": [
    "Falco Event Forwarder",
    "Falco Response Engine",
    "Falco Alert Router",
    "Falco Output Connector"
   ]
  },
  "AST_e464fa8a": {
   "name": "Tracee (eBPF Runtime Security and Forensics)",
   "type": "framework",
   "source": "https://github.com/aquasecurity/tracee",
   "aliases": [
    "Aqua Tracee",
    "Tracee Runtime Security",
    "eBPF Forensics",
    "Tracee Threat Detection"
   ]
  },
  "AST_36382965": {
   "name": "auditd Privilege Escalation Detection Ruleset",
   "type": "tool",
   "source": "https://github.com/linux-audit/audit-userspace",
   "aliases": [
    "auditd PE Rules",
    "Linux Audit Runtime Detection",
    "auditd Privilege Escalation Ruleset",
    "Audit Threat Detection Rules"
   ]
  },
  "AST_f8f83214": {
   "name": "STOT",
   "type": "model",
   "source": "https://github.com/Maithili/SpatioTemporalObjectTracking",
   "aliases": [
    "SpatioTemporalObjectTracking",
    "Graph Translation Network for Object Dynamics"
   ]
  },
  "AST_40fe4dc0": {
   "name": "SLaTe-PRO",
   "type": "model",
   "source": "https://github.com/Maithili/SLaTe-PRO",
   "aliases": [
    "Sequential Latent Temporal model for Predicting Routine Object usage"
   ]
  },
  "AST_5cae94b3": {
   "name": "GLOBE",
   "type": "framework",
   "source": "https://github.com/PaInt-Lab/GLOBE",
   "aliases": [
    "uncertainty-Guided LLM reasoning for routine Object prediction via Behavioral tEmporal modeling"
   ]
  },
  "AST_67ae4f55": {
   "name": "HOMER Dataset",
   "type": "dataset",
   "source": "https://github.com/GT-RAIL/rail_tasksim/tree/homer/routines",
   "aliases": [
    "HOMER+",
    "HOMER-Noise",
    "Household Object Movements from Everyday Routines"
   ]
  },
  "AST_222465dc": {
   "name": "HOI4ABOT",
   "type": "model",
   "source": "https://evm7.github.io/HOI4ABOT_page/",
   "aliases": [
    "HOI4ABOT",
    "Human-Object Interaction Anticipation for Assistive roBOTs"
   ]
  },
  "AST_709253da": {
   "name": "NIABench",
   "type": "benchmark",
   "source": "https://github.com/Cognition2Action-Lab/NIABench",
   "aliases": [
    "NIABench",
    "Non-Intrusive Assistance Benchmark",
    "Assistance Without Interruption"
   ]
  },
  "AST_e3116d3a": {
   "name": "NaRR",
   "type": "framework",
   "source": "https://github.com/Cognition2Action-Lab/NIABench",
   "aliases": [
    "NaRR",
    "Non-intrusive Assistant via Retrieval and Ranking",
    "LLM-ranker hybrid assistance"
   ]
  },
  "AST_205d4b2f": {
   "name": "AURA",
   "type": "framework",
   "source": "https://www.mdpi.com/1424-8220/26/12/xxxx（Sensors 2026论文DOI[待核查]）",
   "aliases": [
    "AURA",
    "Agent-based Unified Robot Assistance",
    "SOP-grounded LLM assistance framework"
   ]
  },
  "AST_2a8869cb": {
   "name": "ViLing-MMT",
   "type": "model",
   "source": "https://arxiv.org/abs/2310.02506",
   "aliases": [
    "ViLing-MMT",
    "Visuo-Lingual Multimodal Transformer",
    "Proactive HRI Visuo-Lingual Transformer"
   ]
  },
  "AST_52cbe8ff": {
   "name": "NeuroCommitSSM",
   "type": "model",
   "source": "https://github.com/madibabaiasl/NeuroCommitSSM",
   "aliases": [
    "NeuroCommitSSM",
    "EEG-EMG-ET Commit Readiness",
    "madibabaiasl/NeuroCommitSSM",
    "HAC supervisor"
   ]
  },
  "AST_9d0e29f9": {
   "name": "NeuroCommitSSM EEG-EMG-ET Dataset",
   "type": "dataset",
   "source": "https://github.com/madibabaiasl/NeuroCommitSSM",
   "aliases": [
    "NeuroCommitSSM Dataset",
    "ICF-ADL EEG-EMG-ET Dataset",
    "tri-modal ADL intent dataset"
   ]
  },
  "AST_a03489d3": {
   "name": "MediaPipe Holistic",
   "type": "model",
   "source": "https://ai.google.dev/edge/mediapipe/solutions/vision/holistic_landmarker",
   "aliases": [
    "MediaPipe Whole-Body Landmarker"
   ]
  },
  "AST_67b1baa8": {
   "name": "A Random-Finite-Set Approach to Bayesian SLAM (PHD-SLAM)",
   "type": "paper",
   "source": "https://doi.org/10.1109/TRO.2011.2141690",
   "aliases": [
    "Mullane 2011 RFS-SLAM",
    "PHD-SLAM T-RO 2011",
    "SLAM gets a PHD"
   ]
  },
  "AST_66d031ea": {
   "name": "OpenPRA",
   "type": "framework",
   "source": "https://openpra.org",
   "aliases": [
    "OpenPRA Framework",
    "OpenPRA Initiative"
   ]
  },
  "AST_606611a0": {
   "name": "Bayesian_Hilbert_Maps",
   "type": "package",
   "source": "https://github.com/RansML/Bayesian_Hilbert_Maps",
   "aliases": [
    "BHM",
    "sbhm",
    "Bayesian Hilbert Maps Python",
    "RansML BHM"
   ]
  },
  "AST_e6fe02d3": {
   "name": "ds_k3dom",
   "type": "ros_package",
   "source": "https://github.com/JuyeopHan/dsk3dom_public",
   "aliases": [
    "DS-K3DOM",
    "dsk3dom",
    "DS K3DOM"
   ]
  },
  "AST_37a56d4a": {
   "name": "ProcTHOR Framework",
   "type": "framework",
   "source": "https://github.com/allenai/procthor",
   "aliases": [
    "ProcTHOR"
   ]
  },
  "AST_84f6e5f1": {
   "name": "Holodeck",
   "type": "framework",
   "source": "https://github.com/allenai/Holodeck",
   "aliases": [
    "allenai/Holodeck",
    "Holodeck (AI2)"
   ]
  },
  "AST_c4eaeb06": {
   "name": "webgl-noise",
   "type": "package",
   "source": "https://github.com/ashima/webgl-noise",
   "aliases": [
    "Ashima Arts GLSL Noise",
    "stegu/webgl-noise",
    "GLSL Noise Routines for WebGL"
   ]
  },
  "AST_3dffff62": {
   "name": "glsl-noise",
   "type": "package",
   "source": "https://github.com/hughsk/glsl-noise",
   "aliases": [
    "hughsk/glsl-noise",
    "npm glsl-noise",
    "glslify noise"
   ]
  },
  "AST_7fac5ba0": {
   "name": "Babylon.js ProceduralTexture",
   "type": "framework",
   "source": "https://doc.babylonjs.com/features/featuresDeepDive/materials/using/proceduralTextures/",
   "aliases": [
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    "Rodz Labs Material Maker",
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    "MM"
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   "source": "[待核查：CMU RI 官网 URL]",
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    "Jueying Lite Backflip Data",
    "四足机器人后空翻数据集"
   ]
  },
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   "name": "Solo 8 Robot (ODRI)",
   "type": "robot",
   "source": "https://open-dynamic-robot-initiative.github.io/",
   "aliases": [
    "Solo 8",
    "ODRI Solo",
    "Open Dynamic Robot Initiative quadruped"
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   "source": "https://doi.org/10.1177/0278364915626501",
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   "source": "https://doi.org/10.1109/ICRA.2014.6907389",
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   "source": "https://dspace.mit.edu/handle/1721.1/138000.2",
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   "source": "https://arxiv.org/abs/1909.06586",
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   "source": "https://openreview.net/forum?id=dPX6K1QHSk",
   "aliases": []
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   "source": "https://doi.org/10.1109/MRA.2024.3487322",
   "aliases": []
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   "source": "https://research.google/pubs/sim-to-real-learning-agile-locomotion-for-quadruped-robots/",
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  },
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   "name": "Raibert 1986 Book",
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   "source": "https://mitpress.mit.edu/9780262181176/legged-robots-that-balance/",
   "aliases": []
  },
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   "type": "model",
   "source": "https://doi.org/10.3390/biomimetics9010024",
   "aliases": []
  },
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   "source": "https://doi.org/10.1177/0278364906064567",
   "aliases": []
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   "source": "https://doi.org/10.1177/0278364917751250",
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  },
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   "aliases": [
    "Cheng Xuxin Extreme Parkour",
    "RSS 2024 Parkour"
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  },
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   "name": "OpenCat",
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   "source": "https://github.com/PetoiCamp/OpenCat",
   "aliases": [
    "Petoi OpenCat",
    "Nybble Bittle"
   ]
  },
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   "source": "https://github.com/mit-biomimetics/haptic_transformer",
   "aliases": [
    "HAPTR2",
    "Haptic Transformer",
    "Brooks 2022"
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  },
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   "name": "cpg_quadruped_control",
   "type": "package",
   "source": "https://github.com/leggedrobotics/cpg_control（示例地址，实际需根据具体实现选择）",
   "aliases": [
    "Hopf CPG",
    "Matsuoka CPG",
    "Kuramoto Oscillator Network"
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  },
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   "name": "rl_locomotion (RMA)",
   "type": "package",
   "source": "https://github.com/antonilo/rl_locomotion",
   "aliases": [
    "antonilo/rl_locomotion",
    "RMA RaiSim",
    "RMA training code"
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  },
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   "source": "https://lcm-proj.github.io/",
   "aliases": []
  },
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   "name": "Hwangbo et al. 2019 (Science Robotics)",
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   "source": "https://www.science.org/doi/10.1126/scirobotics.aau5872",
   "aliases": [
    "ANYmal RL 2019",
    "Science Robotics ANYmal",
    "Hwangbo Learned Actuator"
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   "source": "https://github.com/tensorflow/model-optimization",
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    "TFMOT",
    "tf-model-optimization"
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  },
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   "source": "https://github.com/NVIDIA/TensorRT-Model-Optimizer",
   "aliases": [
    "TensorRT Model Optimizer",
    "ModelOpt",
    "mtq",
    "NVIDIA ModelOpt"
   ]
  },
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   "name": "Gemma 3 QAT Models",
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   "source": "https://huggingface.co/google/gemma_3_4b_qat",
   "aliases": [
    "Gemma 3 QAT",
    "google/gemma-3-qat",
    "Gemma3 INT4"
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  },
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   "source": "https://arxiv.org/abs/2206.10787",
   "aliases": [
    "Quasi-Dynamic Contact Smoothing Planning",
    "CQDC Planning",
    "Pang2023TRO"
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  },
  "AST_318aded0": {
   "name": "cddlib",
   "type": "package",
   "source": "https://github.com/cddlib/cddlib",
   "aliases": [
    "cdd",
    "CDD",
    "Double Description Method Library",
    "pycddlib",
    "Fukuda cddlib"
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  },
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   "name": "Contact Mode Guided Motion Planning for Quasidynamic Dexterous Manipulation in 3D",
   "type": "paper",
   "source": "https://arxiv.org/abs/2105.14431",
   "aliases": [
    "CMGMP 3D",
    "Cheng2022ICRA",
    "CMGMP ICRA2022",
    "Contact Mode Guided 3D"
   ]
  },
  "AST_d91bdbbe": {
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  },
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  },
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  },
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   "source": "[待核查]",
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  },
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  },
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  },
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  },
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    "Retrieval-Augmented Generation Benchmark",
    "RAG能力基准"
   ]
  },
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  },
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    "medical RAG benchmark",
    "医疗RAG评估"
   ]
  },
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   "source": "https://arxiv.org/abs/2401.15391",
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    "multi-hop RAG benchmark",
    "多跳RAG评估"
   ]
  },
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   "source": "https://github.com/project-miracl/nomiracl",
   "aliases": [
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    "noMIRACL",
    "non-relevant MIRACL",
    "MIRACL non-relevant"
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  },
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   "source": "https://github.com/Arize-ai/phoenix",
   "aliases": [
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    "Arize Phoenix",
    "Arize-ai/phoenix",
    "arize-phoenix"
   ]
  },
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   "name": "SimuRLacra",
   "type": "framework",
   "source": "https://github.com/famura/SimuRLacra",
   "aliases": [
    "SimuRLacra",
    "Pyrado",
    "RcsPySim",
    "famura/SimuRLacra"
   ]
  },
  "AST_e33bb397": {
   "name": "Ray Tune",
   "type": "framework",
   "source": "https://github.com/ray-project/ray",
   "aliases": [
    "Ray PBT",
    "Ray PB2",
    "ray.tune.schedulers.PopulationBasedTraining",
    "ray.tune.schedulers.pb2.PB2"
   ]
  },
  "AST_a3dc1fbc": {
   "name": "VerifAI",
   "type": "tool",
   "source": "https://github.com/BerkeleyLearnVerify/VerifAI",
   "aliases": []
  },
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   "name": "ScenicNL",
   "type": "tool",
   "source": "https://arxiv.org/abs/2405.03709",
   "aliases": []
  },
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   "name": "Dr.Jit",
   "type": "framework",
   "source": "https://github.com/mitsuba-renderer/drjit",
   "aliases": [
    "drjit",
    "Dr.Jit",
    "DrJit",
    "JIT compiler for differentiable rendering"
   ]
  },
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   "name": "Intel Open Image Denoise (OIDN)",
   "type": "framework",
   "source": "https://github.com/OpenImageDenoise/oidn",
   "aliases": [
    "OIDN",
    "Intel Open Image Denoise",
    "openimagedenoise"
   ]
  },
  "AST_9abce5de": {
   "name": "mitransient",
   "type": "package",
   "source": "https://github.com/diegoroyo/mitransient",
   "aliases": [
    "mitransient",
    "transient Mitsuba 3",
    "NLOS rendering"
   ]
  },
  "AST_cec24f51": {
   "name": "SmallVCM",
   "type": "framework",
   "source": "https://github.com/SmallVCM/SmallVCM",
   "aliases": [
    "SmallVCM",
    "VCM reference implementation",
    "Vertex Connection and Merging implementation"
   ]
  },
  "AST_c3a3f198": {
   "name": "eProsima Fast DDS Security Plugins",
   "type": "framework",
   "source": "https://github.com/eProsima/Fast-DDS",
   "aliases": [
    "FastDDS Security",
    "Fast-RTPS Security"
   ]
  },
  "AST_f315ead8": {
   "name": "Open Policy Agent Gatekeeper",
   "type": "framework",
   "source": "https://github.com/open-policy-agent/gatekeeper",
   "aliases": [
    "open-policy-agent/gatekeeper",
    "OPA Gatekeeper",
    "K8s Policy Controller"
   ]
  },
  "AST_ceb9dd68": {
   "name": "Kubernetes RBAC Authorization API",
   "type": "framework",
   "source": "https://kubernetes.io/docs/reference/access-authn-authz/rbac/",
   "aliases": [
    "K8s RBAC API",
    "Kubernetes RBAC",
    "rbac.authorization.k8s.io"
   ]
  },
  "AST_68cda7b7": {
   "name": "Octanas Reactive Wall Following",
   "type": "package",
   "source": "[待核查]",
   "aliases": [
    "Octanas subsumption",
    "reactive wall following python"
   ]
  },
  "AST_7c7bc2dc": {
   "name": "rbarbulescu PID Wall Following",
   "type": "package",
   "source": "[待核查]",
   "aliases": [
    "rbarbulescu PID wall following",
    "Pioneer-3DX wall following"
   ]
  },
  "AST_d6c518d4": {
   "name": "robertandreibarbulescu PID wall following",
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   "source": "https://github.com/robertandreibarbulescu/pid-wall-following",
   "aliases": [
    "robertandreibarbulescu PID",
    "Pioneer-3DX VREP wall following"
   ]
  },
  "AST_56ec8cfb": {
   "name": "boids4R",
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   "source": "https://github.com/fbertran/boids4R",
   "aliases": [
    "boids for R",
    "Reynolds boids R"
   ]
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  "AST_dae365c3": {
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   "type": "paper",
   "source": "https://arxiv.org/abs/2302.12863",
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    "Senbaslar RLSS",
    "Linear Spatial Separations",
    "arXiv 2302.12863"
   ]
  },
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   "name": "agn-7 bugs",
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   "source": "https://github.com/agn-7/bugs",
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    "agn-7/bugs",
    "bug0 bug1 bug2 ROS"
   ]
  },
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   "name": "BUG2_sim",
   "type": "package",
   "source": "https://github.com/buenos-dan/BUG2_sim",
   "aliases": [
    "buenos-dan BUG2_sim",
    "Bug2 STM32 simulation"
   ]
  },
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   "name": "Lumelsky Stepanov 1987 Bug1 Bug2",
   "type": "model",
   "source": "https://link.springer.com/article/10.1007/BF02187822",
   "aliases": [
    "Lumelsky Stepanov Bug Algorithm 1987"
   ]
  },
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   "name": "Kamon Rimon Rivlin 1998 Tangent Bug",
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   "source": "https://journals.sagepub.com/doi/10.1177/027836499801700906",
   "aliases": [
    "Tangent Bug 1998",
    "Kamon TangentBug IJRR"
   ]
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   "name": "MATLAB Navigation Toolbox controllerVFH",
   "type": "tool",
   "source": "https://www.mathworks.com/help/nav/ref/controllervfh-system-object.html",
   "aliases": [
    "controllerVFH",
    "MATLAB VFH",
    "MathWorks VFH"
   ]
  },
  "AST_0cf8d7c4": {
   "name": "lijun-mce/vfh_local_planner",
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   "source": "https://github.com/lijun-mce/vfh_local_planner",
   "aliases": [
    "vfh_local_planner",
    "ROS2 VFH planner"
   ]
  },
  "AST_53e9b0e2": {
   "name": "Botix C Robotics Framework",
   "type": "framework",
   "source": "https://sourceforge.net/projects/botix/",
   "aliases": [
    "Botix C Framework",
    "Botix Subsumption Framework",
    "vorik2005/botix"
   ]
  },
  "AST_07db3fc5": {
   "name": "Robotics Toolbox for MATLAB (sl_braitenberg)",
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   "source": "https://github.com/petercorke/robotics-toolbox-matlab",
   "aliases": [
    "RTB MATLAB Braitenberg",
    "sl_braitenberg Simulink",
    "Corke Braitenberg simulation"
   ]
  },
  "AST_99b2e8f1": {
   "name": "EV3 Braitenberg Vehicle Python",
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   "source": "https://qiita.com/domutoro406/items/c52892b5afd2de34d0fd",
   "aliases": [
    "LEGO EV3 Braitenberg",
    "domutoro406 EV3 Braitenberg",
    "ev3dev Braitenberg Python"
   ]
  },
  "AST_3f343a3c": {
   "name": "Raspberry Pi Braitenberg Vehicle",
   "type": "package",
   "source": "CSDN资源（靳骁曈，2025-01-12）",
   "aliases": [
    "RasPi Braitenberg",
    "靳骁曈 Braitenberg",
    "Raspberry Pi Braitenberg vehicle"
   ]
  },
  "AST_f6827631": {
   "name": "Gazebo_Braitenberg_Robot",
   "type": "package",
   "source": "CSDN资源（荒腔走兽，2025-03-28）",
   "aliases": [
    "ROS Gazebo Braitenberg",
    "braitenberg_controller.cpp",
    "Gazebo Braitenberg Robot"
   ]
  },
  "AST_cdbe110c": {
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   "source": "V. Braitenberg, 'Vehicles: Experiments in Synthetic Psychology,' MIT Press, 1984. ISBN: 0262022074",
   "aliases": [
    "Braitenberg 1984",
    "Vehicles Experiments Synthetic Psychology",
    "Braitenberg vehicles book"
   ]
  },
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   "source": "https://arxiv.org/abs/2312.07828",
   "aliases": [
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    "safe_rl"
   ]
  },
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   "source": "https://github.com/SICKAG/sick_safetyscanners2",
   "aliases": [
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    "SICK ROS2 driver"
   ]
  },
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   "name": "SaRA shield",
   "type": "package",
   "source": "https://arxiv.org/abs/2412.10180",
   "aliases": [
    "SaRA shield",
    "SARA shield",
    "Safe Autonomous Reachability Analysis shield"
   ]
  },
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   "name": "Latent Safety Filters",
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   "source": "https://arxiv.org/abs/2502.00935",
   "aliases": [
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    "Latent-Space Reachability",
    "Nakamura Bajcsy Safety Filter",
    "arXiv:2502.00935"
   ]
  },
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   "type": "package",
   "source": "https://proceedings.mlr.press/v305/seo25a.html",
   "aliases": [
    "UNISafe",
    "Uncertainty-aware Latent Safety Filter",
    "Seo Bajcsy OOD Safety"
   ]
  },
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   "type": "package",
   "source": "https://arxiv.org/abs/2509.19555",
   "aliases": [
    "AnySafe",
    "Constraint-Parameterized Latent Safety Filter",
    "Agrawal Bajcsy Runtime Adaptation"
   ]
  },
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   "name": "MoViNet (TensorFlow Model Garden)",
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   "source": "https://github.com/tensorflow/models/tree/master/official/projects/movinet",
   "aliases": [
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    "TensorFlow MoViNet",
    "movinet official"
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  },
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   "name": "TF Hub MoViNet Pre-trained Models",
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   "source": "https://tfhub.dev/google/collections/movinet",
   "aliases": [
    "TF Hub MoViNet",
    "MoViNet SavedModel",
    "MoViNet TFLite models"
   ]
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   "name": "TensorFlow Lite Video Classification Example",
   "type": "tool",
   "source": "https://www.tensorflow.org/lite/examples/video_classification/overview",
   "aliases": [
    "TFLite video classification demo",
    "Android video classifier",
    "MoViNet Android example"
   ]
  },
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   "name": "fastdtw",
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   "source": "https://github.com/slaypni/fastdtw",
   "aliases": [
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    "fastdtw-python"
   ]
  },
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   "name": "YOLACT/YOLACT++ Model Weights",
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   "source": "https://github.com/dbolya/yolact",
   "aliases": [
    "YOLACT",
    "YOLACT++",
    "dbolya/yolact"
   ]
  },
  "AST_27cf5df8": {
   "name": "YOLACT/YOLACT++ Source Code",
   "type": "tool",
   "source": "https://github.com/dbolya/yolact",
   "aliases": [
    "YOLACT code"
   ]
  },
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   "name": "BlendMask Model",
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   "source": "https://github.com/aim-uofa/AdelaiDet",
   "aliases": [
    "BlendMask"
   ]
  },
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   "name": "SOLOv2 Model Weights",
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   "source": "https://github.com/WXinlong/SOLO",
   "aliases": [
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    "WXinlong/SOLO"
   ]
  },
  "AST_988a9d22": {
   "name": "SOLO/SOLOv2 Source Code (mmdetection)",
   "type": "tool",
   "source": "https://github.com/WXinlong/SOLO",
   "aliases": [
    "SOLO code"
   ]
  },
  "AST_3b665c36": {
   "name": "SparseInst Model Weights",
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   "source": "https://github.com/hustvl/SparseInst",
   "aliases": [
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    "hustvl/SparseInst",
    "IAM segmentation"
   ]
  },
  "AST_2f291b64": {
   "name": "SparseInst Source Code",
   "type": "tool",
   "source": "https://github.com/hustvl/SparseInst",
   "aliases": [
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   ]
  },
  "AST_927bb15b": {
   "name": "RTMDet-Ins Model",
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   "source": "https://github.com/open-mmlab/mmdetection",
   "aliases": [
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    "RTMDet instance"
   ]
  },
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   "name": "TensorRT-YOLOv8 C++ Deployment",
   "type": "tool",
   "source": "https://gitee.com/chccc1994/TensorRT-YOLOv8",
   "aliases": [
    "TensorRT-YOLOv8",
    "TRT YOLOv8"
   ]
  },
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   "name": "BLASFEO",
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   "source": "https://github.com/giaf/blasfeo",
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    "BLASFEO",
    "Basic Linear Algebra Subroutines For Embedded Optimization"
   ]
  },
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   "name": "CVXGEN",
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   "source": "https://github.com/cvxgen/cvxgen",
   "aliases": [
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    "cvxgen"
   ]
  },
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   "source": "https://github.com/MayiaLab/AutoGenU",
   "aliases": [
    "AutoGenU",
    "C/GMRES codegen"
   ]
  },
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   "name": "NMPCM",
   "type": "framework",
   "source": "https://github.com/aralab-unr/NMPCM",
   "aliases": [
    "NMPCM",
    "NMPC on MCU"
   ]
  },
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   "name": "TinyMPC",
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   "source": "https://github.com/TinyMPC/TinyMPC",
   "aliases": [
    "TinyMPC",
    "tinympc"
   ]
  },
  "AST_ab3ce9d5": {
   "name": "Conic-TinyMPC",
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   "source": "https://github.com/TinyMPC/TinyMPC",
   "aliases": [
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    "conic tinympc"
   ]
  },
  "AST_9f4252be": {
   "name": "AERO-MPPI",
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   "source": "https://github.com/XinChen-stars/AERO_MPPI",
   "aliases": [
    "AERO-MPPI",
    "AERO MPPI"
   ]
  },
  "AST_2a43f0ec": {
   "name": "log-MPPI_ros",
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   "source": "https://github.com/CBx320/log-MPPI_ros",
   "aliases": [
    "log-MPPI_ros",
    "log-MPPI",
    "logMPPI"
   ]
  },
  "AST_96c63378": {
   "name": "MMYOLO",
   "type": "framework",
   "source": "https://github.com/open-mmlab/mmyolo",
   "aliases": [
    "OpenMMLab YOLO"
   ]
  },
  "AST_2cd08a66": {
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   "type": "framework",
   "source": "https://github.com/google-research/deeplab2",
   "aliases": [
    "DeepLab2 framework",
    "Panoptic-DeepLab TF2",
    "google-research/deeplab2",
    "kMaX-DeepLab TF2"
   ]
  },
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   "name": "EfficientPS",
   "type": "framework",
   "source": "https://github.com/DeepSceneSeg/EfficientPS",
   "aliases": [
    "DeepSceneSeg/EfficientPS",
    "EfficientPS Official",
    "EfficientPS PyTorch"
   ]
  },
  "AST_fee4f70e": {
   "name": "PaddleSeg PanopticDeepLab",
   "type": "framework",
   "source": "https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/contrib/PanopticDeepLab",
   "aliases": [
    "PaddleSeg PanopticDeepLab",
    "PaddlePaddle Panoptic-DeepLab"
   ]
  },
  "AST_cd2ce54e": {
   "name": "TRI-ML realtime_panoptic",
   "type": "framework",
   "source": "https://github.com/TRI-ML/realtime_panoptic",
   "aliases": [
    "TRI-ML/realtime_panoptic",
    "Dense Detections Realtime Panoptic"
   ]
  },
  "AST_5211a347": {
   "name": "MobileNetV3 (Large + Small)",
   "type": "model",
   "source": "https://www.tensorflow.org/api_docs/python/tf/keras/applications/MobileNetV3Large",
   "aliases": [
    "MobileNetV3-Large",
    "MobileNetV3-Small",
    "MNv3-L",
    "MNv3-S",
    "tf.keras MobileNetV3"
   ]
  },
  "AST_d28249e0": {
   "name": "cityscapesScripts",
   "type": "package",
   "source": "https://github.com/mcordts/cityscapesScripts",
   "aliases": [
    "mcordts/cityscapesScripts",
    "cityscapesscripts",
    "csCreatePanopticImgs"
   ]
  },
  "AST_05e3ff3e": {
   "name": "RTMO",
   "type": "model",
   "source": "https://github.com/open-mmlab/mmpose/tree/main/projects/rtmo",
   "aliases": [
    "RTMO",
    "Real-Time Multi-person One-stage"
   ]
  },
  "AST_b33a7646": {
   "name": "MoveNet (TensorFlow Lite)",
   "type": "model",
   "source": "https://www.tensorflow.org/lite/examples/pose_estimation/overview",
   "aliases": [
    "MoveNet Lightning",
    "MoveNet Thunder",
    "TFLite Pose"
   ]
  },
  "AST_6c36414d": {
   "name": "PP-TinyPose (PaddleDetection)",
   "type": "model",
   "source": "https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/tiny_pose",
   "aliases": [
    "TinyPose",
    "PP-TinyPose",
    "PaddleDetection TinyPose"
   ]
  },
  "AST_d8fc40ca": {
   "name": "Lite-HRNet",
   "type": "model",
   "source": "https://github.com/HRNet/Lite-HRNet",
   "aliases": [
    "LiteHRNet",
    "Conditional Channel Weighting Net"
   ]
  },
  "AST_ac1fc54e": {
   "name": "rtmlib",
   "type": "tool",
   "source": "https://github.com/Tau-J/rtmlib",
   "aliases": [
    "rtmlib",
    "Tau-J rtmlib",
    "lightweight RTMPose inference"
   ]
  },
  "AST_89165ab3": {
   "name": "RTMDet",
   "type": "model",
   "source": "https://github.com/open-mmlab/mmdetection/tree/main/configs/rtmdet",
   "aliases": [
    "RTMDet-nano",
    "RTMDet-s",
    "Real-time Models for Detection"
   ]
  },
  "AST_9b9c8f50": {
   "name": "SmoothNet",
   "type": "model",
   "source": "https://github.com/cure-lab/SmoothNet",
   "aliases": [
    "SmoothNet MLP",
    "cure-lab/SmoothNet",
    "Plug-and-Play Pose Smoothing Network"
   ]
  },
  "AST_0a584e20": {
   "name": "LaCAM",
   "type": "tool",
   "source": "https://github.com/Kei18/lacam",
   "aliases": [
    "LaCAM",
    "Lazy Constraints Addition Search"
   ]
  },
  "AST_ae042e71": {
   "name": "Efficient-Segmentation-Networks",
   "type": "package",
   "source": "https://github.com/xiaoyufenfei/Efficient-Segmentation-Networks",
   "aliases": [
    "Efficient Segmentation Networks",
    "xiaoyufenfei Efficient-Segmentation-Networks"
   ]
  },
  "AST_bddab5a0": {
   "name": "PaddleSeg",
   "type": "framework",
   "source": "https://github.com/PaddlePaddle/PaddleSeg",
   "aliases": [
    "PaddleSeg",
    "PP-LiteSeg"
   ]
  },
  "AST_c8a15b01": {
   "name": "isaac_ros_image_segmentation",
   "type": "package",
   "source": "https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_image_segmentation",
   "aliases": [
    "Isaac ROS Image Segmentation",
    "NITROS Segmentation",
    "isaac_ros_image_segmentation"
   ]
  },
  "AST_3ebb752b": {
   "name": "PROFIsafe",
   "type": "framework",
   "source": "https://www.profisafe.net/",
   "aliases": [
    "CPF3 safety",
    "F-Host F-Device",
    "PROFINET safety",
    "PROFIsafe V2",
    "black channel safety protocol"
   ]
  },
  "AST_ed21f09f": {
   "name": "SICK microScan3 Safety Laser Scanner",
   "type": "tool",
   "source": "https://www.sick.com/",
   "aliases": [
    "SICK microScan3 safeHDDM",
    "microScan3 Safety Scanner"
   ]
  },
  "AST_50ed512a": {
   "name": "Pilz PSENscan Safety Laser Scanner",
   "type": "framework",
   "source": "https://www.pilz.com/en-US/products/sensor-systems/safety-laser-scanners/psenscan",
   "aliases": [
    "PSENscan",
    "PSENscan 安全激光扫描仪"
   ]
  },
  "AST_487c6389": {
   "name": "psen_scan_v2",
   "type": "tool",
   "source": "https://github.com/PilzDE/psen_scan_v2",
   "aliases": [
    "PSENscan ROS driver",
    "PSENscan driver",
    "Pilz scan driver",
    "psen_scan_v2"
   ]
  },
  "AST_a450c5fa": {
   "name": "Active Safety Envelopes using Light Curtains with Probabilistic Guarantees",
   "type": "framework",
   "source": "https://arxiv.org/abs/2107.04000",
   "aliases": [
    "Ancha 2021",
    "CMU PLC safety",
    "CMU-MFI plc-safety",
    "Programmable Light Curtains",
    "Safety Envelopes Light Curtains",
    "plc-safety"
   ]
  },
  "AST_642692e6": {
   "name": "Light Curtain Simulator",
   "type": "tool",
   "source": "https://github.com/CMU-Light-Curtains/Simulator",
   "aliases": [
    "CMU-Light-Curtains/Simulator",
    "Light Curtain Sim"
   ]
  },
  "AST_aa98931a": {
   "name": "ConstraintGraph",
   "type": "tool",
   "source": "https://github.com/CMU-Light-Curtains/ConstraintGraph",
   "aliases": [
    "CMU-Light-Curtains/ConstraintGraph",
    "Light Curtain Profile Planning"
   ]
  },
  "AST_fd8bb2cd": {
   "name": "Active Velocity Estimation using Light Curtains via Self-Supervised Multi-Armed Bandits",
   "type": "framework",
   "source": "https://arxiv.org/abs/2306.17902",
   "aliases": [
    "Ancha 2023",
    "Light Curtain MAB"
   ]
  },
  "AST_ca8128da": {
   "name": "Allen-Bradley Guardmaster 440F MatGuard Safety Mat",
   "type": "tool",
   "source": "https://www.rockwellautomation.com/en-us/products/hardware/safety-products/440f-matguard.html",
   "aliases": [
    "440F MatGuard",
    "Guardmaster Safety Mat",
    "AB MatGuard",
    "Rockwell 压敏垫"
   ]
  },
  "AST_af3e9854": {
   "name": "Allen-Bradley 440F MatGuard Mat Manager Control Unit",
   "type": "framework",
   "source": "https://www.rockwellautomation.com/en-us/products/hardware/safety-products/safety-relays-mat.html",
   "aliases": [
    "MatGuard Mat Manager",
    "440F-C28026",
    "440F Mat Controller",
    "AB 压敏垫控制器"
   ]
  },
  "AST_942767f2": {
   "name": "Siemens SIRIUS SMART Safety Relay 3SK0",
   "type": "framework",
   "source": "https://www.siemens.com/en-us/products/sirius/3sk0-smart-safety-relay/",
   "aliases": [
    "3SK0",
    "SIRIUS SMART Safety Relay",
    "Siemens 安全继电器"
   ]
  },
  "AST_7930a255": {
   "name": "pyLiDAR-SLAM",
   "type": "framework",
   "source": "https://github.com/Kitware/pyLiDAR-SLAM",
   "aliases": [
    "Kitware/pyLiDAR-SLAM",
    "LiDAR SLAM with loop closure",
    "CT-ICP Python framework"
   ]
  },
  "AST_f1ed927e": {
   "name": "Linux kernel PREEMPT_RT",
   "type": "framework",
   "source": "https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git",
   "aliases": [
    "PREEMPT_RT kernel",
    "Linux RT kernel",
    "real-time Linux kernel"
   ]
  },
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   "name": "Xenomai 3 Cobalt",
   "type": "framework",
   "source": "https://gitlab.com/xenomai/xenomai3/xenomai",
   "aliases": [
    "Xenomai Cobalt",
    "Xenomai 3",
    "libcobalt",
    "libalchemy",
    "prepare-kernel.sh",
    "xenomai latency tool"
   ]
  },
  "AST_7a9741df": {
   "name": "linux-dovetail",
   "type": "framework",
   "source": "https://gitlab.com/xenomai/linux-dovetail",
   "aliases": [
    "Dovetail",
    "linux-dovetail",
    "out-of-band stage",
    "Dovetail interface"
   ]
  },
  "AST_23297012": {
   "name": "LWD",
   "type": "model",
   "source": "https://arxiv.org/abs/2605.00416",
   "aliases": [
    "Learning While Deploying",
    "LWD",
    "fleet-scale RL"
   ]
  },
  "AST_6c9d4852": {
   "name": "cbf-rl-navigation-demo",
   "type": "package",
   "source": "https://github.com/lzyang2000/cbf-rl-navigation-demo",
   "aliases": [
    "lzyang2000/cbf-rl-navigation-demo",
    "CBF-RL Navigation Demo"
   ]
  },
  "AST_8fc3995d": {
   "name": "GR-RL",
   "type": "model",
   "source": "https://seed.bytedance.com/gr_rl",
   "aliases": [
    "GR-RL",
    "Going dexterous and pRecise for Long-horizon Robotic manipulation",
    "ByteDance Seed GR-RL",
    "GR-3 RL"
   ]
  },
  "AST_cb8a474f": {
   "name": "Online Decision Transformer",
   "type": "model",
   "source": "https://github.com/zwq-ice/online-decision-transformer",
   "aliases": [
    "ODT",
    "Online Decision Transformer",
    "zwq-ice/online-decision-transformer"
   ]
  },
  "AST_07a4c355": {
   "name": "DirectX-Graphics-Samples",
   "type": "framework",
   "source": "https://github.com/microsoft/DirectX-Graphics-Samples",
   "aliases": [
    "D3D12 Raytracing Samples",
    "DirectX Raytracing Samples"
   ]
  },
  "AST_55f9cb44": {
   "name": "Quake II RTX",
   "type": "tool",
   "source": "https://github.com/NVIDIA/Q2RTX",
   "aliases": [
    "Q2RTX",
    "Quake 2 RTX"
   ]
  },
  "AST_4eae39f3": {
   "name": "GfxExp",
   "type": "tool",
   "source": "https://github.com/shocker-0x15/GfxExp",
   "aliases": [
    "GfxExp Rendering Experiments"
   ]
  },
  "AST_7a511ea7": {
   "name": "response-time-analysis",
   "type": "tool",
   "source": "https://lib.rs/crates/response-time-analysis",
   "aliases": []
  },
  "AST_71b554a4": {
   "name": "Bini 2019 dbf Test Point Minimization Code",
   "type": "tool",
   "source": "[待核查]",
   "aliases": []
  },
  "AST_3dd84748": {
   "name": "LITMUS-RT",
   "type": "framework",
   "source": "https://litmus-rt.org",
   "aliases": []
  },
  "AST_e86efd62": {
   "name": "ARINC 653",
   "type": "paper",
   "source": "https://www.sae.org/standards/content/arinc653p1-6-2024/",
   "aliases": []
  },
  "AST_60a5b78c": {
   "name": "EMQX Neuron",
   "type": "framework",
   "source": "https://github.com/emqx/neuron",
   "aliases": [
    "Neuron",
    "EMQX Neuron",
    "industrial connectivity server",
    "neuron gateway"
   ]
  },
  "AST_79e58cb4": {
   "name": "Omniverse Nucleus",
   "type": "framework",
   "source": "https://www.nvidia.com/en-us/omniverse/",
   "aliases": [
    "Nucleus Server",
    "Omniverse Nucleus",
    "Nucleus Cloud",
    "Live Sync server"
   ]
  },
  "AST_e6bfdbb0": {
   "name": "FMI Standard (Modelica Association)",
   "type": "framework",
   "source": "https://github.com/modelica/fmi-standard",
   "aliases": [
    "FMI",
    "Functional Mock-up Interface",
    "FMU standard",
    "FMI 3.0",
    "Modelica Association FMI"
   ]
  },
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   "name": "ManipArena",
   "type": "benchmark",
   "source": "https://github.com/maniparena/maniparena-repo",
   "aliases": [
    "ManipArena Benchmark"
   ]
  },
  "AST_83d80491": {
   "name": "RoboChallenge",
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   "source": "https://robochallenge.cn",
   "aliases": [
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   ]
  },
  "AST_ade04d89": {
   "name": "EAI Bench",
   "type": "benchmark",
   "source": "https://aihub.caict.ac.cn/docs/7E6SoNH5ZZvh",
   "aliases": [
    "EAI-Bench"
   ]
  },
  "AST_1960ddf3": {
   "name": "EIBench",
   "type": "benchmark",
   "source": "https://kfqgw.beijing.gov.cn/ywdt/kjcgzhgd/kjqy/202511/t20251114_4316681.html",
   "aliases": [
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   ]
  },
  "AST_79ea1b71": {
   "name": "RoboArena",
   "type": "benchmark",
   "source": "https://github.com/robo-arena/roboarena",
   "aliases": [
    "RoboArena Benchmark"
   ]
  },
  "AST_2cda7cfe": {
   "name": "ManipulationNet",
   "type": "benchmark",
   "source": "https://github.com/ManipulationNet/mnet_client",
   "aliases": [
    "ManipulationNet Benchmark"
   ]
  },
  "AST_5ad2933c": {
   "name": "SceneReplica",
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   "source": "https://github.com/IRVLUTD/SceneReplica",
   "aliases": [
    "SceneReplica Benchmark"
   ]
  },
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   "name": "Never Stop Learning",
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   "source": "https://research.google/pubs/never-stop-learning-the-effectiveness-of-fine-tuning-in-robotic-reinforcement-learning/",
   "aliases": [
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    "NSL"
   ]
  },
  "AST_d8f785e5": {
   "name": "RTR (Robot-Trains-Robot) Official Implementation",
   "type": "framework",
   "source": "https://github.com/hukz18/Robot-Trains-Robot",
   "aliases": [
    "Robot-Trains-Robot",
    "RTR",
    "hukz18/Robot-Trains-Robot"
   ]
  },
  "AST_25899bc5": {
   "name": "ToddlerBot (Open-Source ML-Compatible Humanoid Platform)",
   "type": "robot",
   "source": "https://github.com/hshi74/toddlerbot",
   "aliases": [
    "ToddlerBot",
    "toddy",
    "hshi74/toddlerbot"
   ]
  },
  "AST_251a7bc7": {
   "name": "SplatR",
   "type": "model",
   "source": "https://arxiv.org/abs/2411.14322",
   "aliases": [
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    "Gaussian Splatting Rearrangement"
   ]
  },
  "AST_b1d2d8b3": {
   "name": "LM-SymOpt",
   "type": "model",
   "source": "https://arxiv.org/abs/2501.15214",
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    "Language Model Symbolic Optimization"
   ]
  },
  "AST_cac129fd": {
   "name": "LASP",
   "type": "model",
   "source": "https://arxiv.org/abs/2407.09792",
   "aliases": [
    "Language-Augmented Symbolic Planner"
   ]
  },
  "AST_86b3f489": {
   "name": "3D Mapping + Semantic Search Rearrangement",
   "type": "model",
   "source": "https://arxiv.org/abs/2210.04784",
   "aliases": [
    "Trabucco Visual Room Rearrangement",
    "Voxel Semantic Map Rearrangement"
   ]
  },
  "AST_2a2c67c8": {
   "name": "Uniform Object Rearrangement: From Complete Monotone Primitives to Efficient Non-Monotone Informed Search",
   "type": "paper",
   "source": "https://arxiv.org/abs/2101.12241",
   "aliases": [
    "Wang/Gao/Nakhimovich/Yu/Bekris 2021",
    "arXiv:2101.12241",
    "Uniform Object Rearrangement ICRA 2021",
    "DFSDP monotone primitive"
   ]
  },
  "AST_209982c2": {
   "name": "Tabletop Object Rearrangement: Structure, Complexity, and Efficient Combinatorial Search-Based Solutions (Gao 2024 PhD Thesis)",
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   "source": "https://arxiv.org/abs/2412.15398",
   "aliases": [
    "Gao PhD 2024",
    "arXiv:2412.15398",
    "TORO TORE TORI ORLA* thesis"
   ]
  },
  "AST_d30f3e98": {
   "name": "RoboPARA: A Novel LLM-Driven Framework for Dual-Arm Cooperative Scheduling Problem",
   "type": "paper",
   "source": "https://arxiv.org/abs/2506.06683",
   "aliases": [
    "Duan et al ICLR 2026 RoboPARA",
    "arXiv:2506.06683",
    "Dual-Arm Cooperative Scheduling Problem"
   ]
  },
  "AST_34bdc623": {
   "name": "libubootenv",
   "type": "tool",
   "source": "https://github.com/sbabic/libubootenv",
   "aliases": [
    "libubootenv",
    "fw_printenv",
    "fw_setenv"
   ]
  },
  "AST_4db9bd60": {
   "name": "OSRL",
   "type": "framework",
   "source": "https://github.com/liuzuxin/OSRL",
   "aliases": [
    "OSRL",
    "liuzuxin/OSRL",
    "Offline Safe RL Library"
   ]
  },
  "AST_c53b4ff5": {
   "name": "nav2_util LifecycleNode",
   "type": "ros_package",
   "source": "https://github.com/ros-navigation/navigation2/tree/main/nav2_util",
   "aliases": [
    "nav2_util LifecycleNode",
    "nav2_util::LifecycleNode",
    "createBond",
    "destroyBond",
    "bond_heartbeat_period"
   ]
  },
  "AST_35f97559": {
   "name": "BIP-ALM",
   "type": "framework",
   "source": "https://github.com/chuanyangjin/MMToM-QA",
   "aliases": [
    "BIP-ALM",
    "Bayesian Inverse Planning Accelerated by Language Models"
   ]
  },
  "AST_f3b4e856": {
   "name": "MuMA-ToM",
   "type": "framework",
   "source": "https://github.com/SCAI-JHU/MuMA-ToM",
   "aliases": [
    "LIMP",
    "Language model-based Inverse Multi-agent Planning"
   ]
  },
  "AST_764d7dff": {
   "name": "MMToM-QA",
   "type": "benchmark",
   "source": "https://github.com/chuanyangjin/MMToM-QA",
   "aliases": [
    "MMToM-QA benchmark"
   ]
  },
  "AST_e4da40f9": {
   "name": "MToMnet",
   "type": "framework",
   "source": "https://arxiv.org/abs/2407.06762",
   "aliases": [
    "MToMnet",
    "Explicit Modelling of ToM for Nonverbal Social Interactions"
   ]
  },
  "AST_0fa14281": {
   "name": "ToMCAT",
   "type": "framework",
   "source": "https://arxiv.org/abs/2502.18438",
   "aliases": [
    "ToMCAT",
    "Theory-of-Mind for Cooperative Agents in Teams"
   ]
  },
  "AST_f175db5e": {
   "name": "K-Level Reasoning (K-R)",
   "type": "framework",
   "source": "https://arxiv.org/abs/2402.01521",
   "aliases": [
    "K-R",
    "K-Level Reasoning with LLMs",
    "recursive strategic reasoning LLM"
   ]
  },
  "AST_14693f52": {
   "name": "K-Level Policy Gradients (KPG)",
   "type": "framework",
   "source": "https://arxiv.org/abs/2509.12117",
   "aliases": [
    "KPG",
    "K-Level Policy Gradients",
    "recursive policy gradient MARL"
   ]
  },
  "AST_a27cf66b": {
   "name": "Recursive Reasoning Graph (R2G)",
   "type": "framework",
   "source": "https://aaai.org/papers/07664-recursive-reasoning-graph-for-multi-agent-reinforcement-learning/",
   "aliases": [
    "R2G",
    "Recursive Reasoning Graph",
    "recursive reasoning MARL"
   ]
  },
  "AST_97cc561d": {
   "name": "Reconstructed Level-k MCTS",
   "type": "framework",
   "source": "https://openreview.net/forum?id=00sD7N1H46",
   "aliases": [
    "Reconstructed Level-k MCTS",
    "Safety-aware Level-k",
    "RLK-MCTS"
   ]
  },
  "AST_15ddcbb7": {
   "name": "Cognitive Hierarchy Model (CH)",
   "type": "framework",
   "source": "https://doi.org/10.1162/0033553041502225",
   "aliases": [
    "CH model",
    "Cognitive Hierarchy",
    "Poisson CH",
    "Camerer 2004"
   ]
  },
  "AST_4e32dcb8": {
   "name": "LLM-Enhanced Hypergame Recursive Reasoners",
   "type": "framework",
   "source": "https://arxiv.org/abs/2502.07443",
   "aliases": [
    "Hypergame LLM Reasoners",
    "Trencsenyi 2025",
    "κ-measure"
   ]
  },
  "AST_e22747e2": {
   "name": "DEL-ToM",
   "type": "framework",
   "source": "https://arxiv.org/abs/2505.17348",
   "aliases": [
    "DEL-ToM",
    "Process Belief Model",
    "PBM",
    "DEL-verifier"
   ]
  },
  "AST_fc66ccef": {
   "name": "Consistent Update Synthesis via Privatized Beliefs",
   "type": "framework",
   "source": "https://arxiv.org/abs/2406.10010",
   "aliases": [
    "Consistent Update Synthesis",
    "Privatized Beliefs",
    "pointed updates",
    "ByzDEL"
   ]
  },
  "AST_11d35dbe": {
   "name": "Belief Contraction in Dynamic Epistemic Logic",
   "type": "framework",
   "source": "https://arxiv.org/abs/2606.31861",
   "aliases": [
    "HPAL",
    "GDEL",
    "Belief Contraction DEL",
    "Belardinelli-Zhang 2026"
   ]
  },
  "AST_39f5f678": {
   "name": "A Study of Belief Revision Postulates in Multi-Agent Systems",
   "type": "framework",
   "source": "https://arxiv.org/abs/2605.02249",
   "aliases": [
    "Multi-Agent AGM",
    "Thielscher-Son 2026",
    "generalized full-meet belief revision"
   ]
  },
  "AST_df3a0ebb": {
   "name": "Baltag-Moss-Solecki DEL Foundations",
   "type": "framework",
   "source": "https://doi.org/10.1007/978-1-4757-2872-9_4",
   "aliases": [
    "Baltag-Moss-Solecki 1998",
    "BMS action model",
    "DEL foundations",
    "product update"
   ]
  },
  "AST_1e41f66d": {
   "name": "SimToM (Think Twice: Perspective-Taking)",
   "type": "framework",
   "source": "https://arxiv.org/abs/2311.10227",
   "aliases": [
    "SimToM",
    "Think Twice Perspective-Taking",
    "Wilf SimToM",
    "two-stage ToM prompting"
   ]
  },
  "AST_0d2612df": {
   "name": "TimeToM",
   "type": "framework",
   "source": "https://arxiv.org/abs/2407.01455",
   "aliases": [
    "TimeToM",
    "Temporal Belief State Chain",
    "TBSC",
    "Time-Aware Belief Solver"
   ]
  },
  "AST_e9bfbfcb": {
   "name": "RecToM (Mind the Perspective)",
   "type": "framework",
   "source": "https://arxiv.org/abs/2606.11724",
   "aliases": [
    "RecToM",
    "Mind the Perspective",
    "recursive perspective construction",
    "KD45 ToM"
   ]
  },
  "AST_0216472c": {
   "name": "SoO Prefilling (Shoes-of-Others Prefilling)",
   "type": "framework",
   "source": "https://aclanthology.org/2026.findings-eacl/",
   "aliases": [
    "SoO prefilling",
    "Shoes-of-Others",
    "Shinoda SoO",
    "prefilling ToM"
   ]
  },
  "AST_c2f7e9b0": {
   "name": "OpenBMC",
   "type": "framework",
   "source": "https://github.com/openbmc/openbmc",
   "aliases": [
    "BMC"
   ]
  },
  "AST_16fc9f10": {
   "name": "SAE ARP4754A",
   "type": "paper",
   "source": "https://www.sae.org/standards/content/arp4754a/",
   "aliases": []
  },
  "AST_784e8ba3": {
   "name": "MPT3",
   "type": "framework",
   "source": "https://github.com/kvasnica/mpt3",
   "aliases": [
    "Multi-Parametric Toolbox"
   ]
  },
  "AST_f72f08ed": {
   "name": "QCAT (Härkegård Control Allocation Toolbox)",
   "type": "framework",
   "source": "https://research.harkegard.se/qcat/about.html",
   "aliases": [
    "QCAT"
   ]
  },
  "AST_0e2c2f17": {
   "name": "Thrust Allocation Control of an Underwater Vehicle with a Redundant Thruster Configuration",
   "type": "paper",
   "source": "https://doi.org/10.3390/math13111766",
   "aliases": []
  },
  "AST_e39d4c89": {
   "name": "FOROS",
   "type": "framework",
   "source": "https://github.com/42dot/foros",
   "aliases": [
    "Failover ROS Framework"
   ]
  },
  "AST_4dd34570": {
   "name": "RoseHA",
   "type": "framework",
   "source": "https://www.rosedata.com/index_en.php/Prodetail/index/proid/1",
   "aliases": []
  },
  "AST_3ef6aef9": {
   "name": "Veritas Cluster Server",
   "type": "framework",
   "source": "https://devopsbyoli.wordpress.com/veritas-cluster-server-vcs/",
   "aliases": [
    "VCS"
   ]
  },
  "AST_1fb1409a": {
   "name": "Barebox bootchooser",
   "type": "framework",
   "source": "https://www.barebox.org/doc/2023.02.0/user/bootchooser.html",
   "aliases": [
    "bootchooser"
   ]
  },
  "AST_b46b6b3f": {
   "name": "rpiRobotics/stereo-sew",
   "type": "tool",
   "source": "https://github.com/rpiRobotics/stereo-sew",
   "aliases": [
    "stereo-sew",
    "SEW angle IK solver"
   ]
  },
  "AST_5dee020d": {
   "name": "utiasSTARS/generative-graphik",
   "type": "tool",
   "source": "https://github.com/utiasSTARS/generative-graphik",
   "aliases": [
    "GGIK",
    "generative graphical IK"
   ]
  },
  "AST_881c3348": {
   "name": "krishauser/Klampt",
   "type": "tool",
   "source": "https://github.com/krishauser/Klampt",
   "aliases": [
    "Klamp't",
    "Kris Hauser robot library"
   ]
  },
  "AST_8892b3eb": {
   "name": "Siemens SIMATIC S7-1500R/H",
   "type": "robot",
   "source": "https://www.siemens.com/global/en/products/automation/systems/industrial/plc/simatic-s7-1500/redundant-and-high-availability-cpus.html",
   "aliases": [
    "S7-1500R/H Redundant PLC",
    "SIMATIC S7-1500R/H"
   ]
  },
  "AST_75156374": {
   "name": "Siemens ET 200SP IM 155-6 PN HF",
   "type": "robot",
   "source": "https://support.industry.siemens.com/cs/cn/zh/view/109815341",
   "aliases": [
    "ET 200SP R1 Interface Module",
    "IM 155-6 PN HF"
   ]
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   "source": "https://doi.org/10.1016/j.asej.2023.102167",
   "aliases": [
    "Aslan 2023 DDQN",
    "Robotis-OP2 Push Recovery"
   ]
  },
  "AST_15a0d010": {
   "name": "voronoi_hsi",
   "type": "ros_package",
   "source": "https://github.com/lucascoelhof/voronoi_hsi",
   "aliases": [
    "lucascoelhof/voronoi_hsi"
   ]
  },
  "AST_dcfe17fa": {
   "name": "MRCPP (Energy-Efficient MRCPP)",
   "type": "framework",
   "source": "https://mrc-pp.github.io/",
   "aliases": [
    "mrc-pp",
    "Raxit MRCPP 2026"
   ]
  },
  "AST_afcbc2f8": {
   "name": "patrolling_sim",
   "type": "ros_package",
   "source": "https://github.com/davidbsp/patrolling_sim",
   "aliases": [
    "davidbsp/patrolling_sim"
   ]
  },
  "AST_41d0f503": {
   "name": "LAVT",
   "type": "model",
   "source": "https://github.com/yz93/LAVT-RIS",
   "aliases": [
    "Language-Aware Vision Transformer",
    "LAVT-RIS"
   ]
  },
  "AST_648e6c03": {
   "name": "X-Decoder",
   "type": "model",
   "source": "https://github.com/microsoft/X-Decoder",
   "aliases": [
    "Generalized Decoder",
    "X-Decoder: Decoder-only Unified Model"
   ]
  },
  "AST_c537f78d": {
   "name": "ReLA",
   "type": "model",
   "source": "https://github.com/henghuiding/ReLA",
   "aliases": [
    "Region-Language Association",
    "GRES Model"
   ]
  },
  "AST_ca4730c9": {
   "name": "CORA OVD",
   "type": "model",
   "source": "https://github.com/tgxs002/CORA",
   "aliases": [
    "CLIP with Learnable Region Prompts",
    "CORA OVD",
    "CORA region prompts",
    "CORA CVPR 2023"
   ]
  },
  "AST_8a41bc6f": {
   "name": "GeomPickPlace",
   "type": "package",
   "source": "https://github.com/mgualti/GeomPickPlace",
   "aliases": [
    "mgualti/GeomPickPlace"
   ]
  },
  "AST_d825cf35": {
   "name": "Planar-Manipulation-via-Learning-Regrasping Dataset (MCB)",
   "type": "dataset",
   "source": "https://github.com/EasonChenXD/Planar-Manipulation-via-Learning-Regrasping",
   "aliases": [
    "pmvlr dataset",
    "MCB stable placements",
    "Planar-Manipulation-via-Learning-Regrasping"
   ]
  },
  "AST_95a20544": {
   "name": "Hocoma ArmeoPower",
   "type": "robot",
   "source": "https://www.hocoma.com/us/solutions/armeo-power/",
   "aliases": [
    "ArmeoPower",
    "Hocoma上肢外骨骼"
   ]
  },
  "AST_e8551442": {
   "name": "Estun JORTmed Single-Joint Series",
   "type": "robot",
   "source": "https://www.estunmedical.com/?list_34/",
   "aliases": [
    "JORTmed",
    "埃斯顿单关节康复"
   ]
  },
  "AST_0162f84d": {
   "name": "CN120022161B Multi-Mode Control Patent",
   "type": "tool",
   "source": "https://m.tianyancha.com/zhuanli/19305d78e52c71c2f9f72f3236d78bd1",
   "aliases": [
    "上海理工多模式专利",
    "CN120022161B"
   ]
  },
  "AST_7a973900": {
   "name": "MIT-Manus Rehabilitation Robot",
   "type": "robot",
   "source": "https://www.inmotionrobotics.com/",
   "aliases": [
    "MIT-Manus",
    "InMotion ARM",
    "MIT-Manus康复机器人",
    "MIT-Manus / InMotion ARM"
   ]
  },
  "AST_7f504d11": {
   "name": "Rehab-Bot (Cognitive Robotics 2025)",
   "type": "robot",
   "source": "https://doi.org/10.1016/j.cogsys.2025.105101",
   "aliases": [
    "Rehab-Bot",
    "ITB康复机器人"
   ]
  },
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   "name": "NVIDIA DeepStream MTMC",
   "type": "framework",
   "source": "https://docs.nvidia.com/mms/text/MDX_Multi_Camera_Tracking_MS_Overview.html",
   "aliases": []
  },
  "AST_3575eff7": {
   "name": "PP-Tracking",
   "type": "framework",
   "source": "https://github.com/PaddlePaddle/PaddleDetection",
   "aliases": []
  },
  "AST_9e78656e": {
   "name": "TransReID",
   "type": "framework",
   "source": "https://github.com/heshuting555/TransReID",
   "aliases": []
  },
  "AST_65863979": {
   "name": "OpenUnReID",
   "type": "framework",
   "source": "https://github.com/open-mmlab/OpenUnReID",
   "aliases": []
  },
  "AST_4fcf9c1c": {
   "name": "SpCL",
   "type": "package",
   "source": "https://github.com/yxgeee/SpCL",
   "aliases": []
  },
  "AST_b26a8e4c": {
   "name": "DWM1001 Module + PANS Firmware",
   "type": "tool",
   "source": "https://www.qorvo.com/products/p/DWM1001",
   "aliases": [
    "Decawave DWM1001",
    "DW1000 module"
   ]
  },
  "AST_6caf4950": {
   "name": "Decawave uwb-core",
   "type": "framework",
   "source": "https://www.qorvo.com/products/p/DW1000",
   "aliases": [
    "uwb-core",
    "Decawave driver"
   ]
  },
  "AST_7acb73c9": {
   "name": "navlie",
   "type": "package",
   "source": "https://github.com/decargroup/navlie",
   "aliases": [
    "decar group navlie"
   ]
  },
  "AST_ba84aa86": {
   "name": "STAR-loc dataset",
   "type": "dataset",
   "source": "https://github.com/utiasASRL/starloc",
   "aliases": [
    "STAR-loc",
    "utiasASRL starloc"
   ]
  },
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   "name": "CREPES: Cooperative Relative Pose Estimation System",
   "type": "paper",
   "source": "https://arxiv.org/abs/2302.01036",
   "aliases": [
    "CREPES paper",
    "浙大高飞 CREPES"
   ]
  },
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   "name": "OCamCalib - Omnidirectional Camera Calibration",
   "type": "tool",
   "source": "https://sites.google.com/site/scarabotix/ocamcalib-toolbox",
   "aliases": [
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   ]
  },
  "AST_669bbae6": {
   "name": "UVDAR - UV Directional Anchor Recognition",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "UVDAR"
   ]
  },
  "AST_4bb44f25": {
   "name": "Active IR/UV LED Marker System",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "IR LED marker",
    "UV LED marker",
    "主动发光标记"
   ]
  },
  "AST_a8a6ee83": {
   "name": "Fisheye / Omnidirectional Camera",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "鱼眼相机",
    "全向相机"
   ]
  },
  "AST_7c44b270": {
   "name": "UWB Transceiver (DW1000/DW3000)",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "DW1000",
    "DW3000",
    "UWB模块"
   ]
  },
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   "name": "SE_2(3) Lie Group Library",
   "type": "tool",
   "source": "[待核查]",
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    "SE_2(3)",
    "extended pose group"
   ]
  },
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   "source": "https://github.com/semantic-release/semantic-release",
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    "semantic release"
   ]
  },
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   "source": "https://github.com/changesets/changesets",
   "aliases": [
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    "@changesets/cli",
    "Changesets"
   ]
  },
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    "@commitlint/cli",
    "conventional-changelog/commitlint"
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    "commitizen/cz-cli"
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  },
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    "conventional-changelog CLI"
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  },
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    "lerna/lerna"
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  },
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   "aliases": [
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    "catkin_prepare_release",
    "ROS1 build system"
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  },
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   "source": "https://github.com/ros-infrastructure/ros_buildfarm",
   "aliases": [
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    "build.ros.org",
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  },
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    "kubevela",
    "OAM Runtime"
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  },
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   "name": "NVIDIA NeMo Megatron Bridge Release Process",
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   "source": "https://docs.nvidia.com/nemo/megatron-bridge/0.5.0/releases/release-process.html",
   "aliases": [
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    "Megatron-Bridge",
    "NeMo release process"
   ]
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   "name": "PEP 602 - Annual Release Cycle for Python",
   "type": "tool",
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    "Python Annual Release Cycle",
    "Python release cadence"
   ]
  },
  "AST_c418c448": {
   "name": "Azure DevOps Release Gates and Approvals",
   "type": "framework",
   "source": "https://learn.microsoft.com/en-us/azure/devops/pipelines/release/approvals/",
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    "Azure Pipelines Gates",
    "Azure DevOps Approvals"
   ]
  },
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   "name": "Microsoft MOF Release Readiness Review Process",
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   "source": "https://learn.microsoft.com/en-us/previous-versions/tn-archive/cc535141(v=technet.10)",
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    "Release Readiness Review",
    "MOF Release Readiness Review"
   ]
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   "name": "Release Go/No-Go Decision Framework for Mobile Teams",
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   "source": "https://www.mobileapplicationtesters.com/resources/release-go-no-go-framework",
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    "Release Go/No-Go Decision Framework",
    "Go No-Go Checklist"
   ]
  },
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   "source": "https://git-scm.com/docs",
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    "git reset",
    "git checkout",
    "Git rollback"
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  },
  "AST_6c2913b7": {
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   "source": "https://github.com/argoproj/argo-cd",
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    "Argo CD self-heal",
    "GitOps rollback"
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  },
  "AST_f0f206ae": {
   "name": "Helm (rollback and history)",
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   "source": "https://helm.sh/docs/",
   "aliases": [
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    "helm history",
    "Helm release rollback"
   ]
  },
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   "source": "https://github.com/USNavalResearchLaboratory/norm",
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    "norm",
    "NORM Toolkit"
   ]
  },
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   "name": "NORM Protocol Specification RFC 5740",
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   "source": "https://www.rfc-editor.org/rfc/rfc5740.html",
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    "NORM Protocol Spec",
    "NORM Transport Protocol"
   ]
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   "name": "Reed-Solomon FEC Schemes RFC 5510",
   "type": "tool",
   "source": "https://www.rfc-editor.org/rfc/rfc5510.html",
   "aliases": [
    "RFC 5510",
    "Reed-Solomon FEC Schemes",
    "GF(2^m) FEC"
   ]
  },
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   "name": "Tetrys Protocol Specification RFC 9407",
   "type": "tool",
   "source": "https://www.rfc-editor.org/rfc/rfc9407.html",
   "aliases": [
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    "Tetrys Protocol Spec",
    "On-the-Fly Network Coding Protocol"
   ]
  },
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   "name": "Technion Network Coding MRS Paper (arXiv:2603.17472v2)",
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   "source": "https://arxiv.org/abs/2603.17472v2",
   "aliases": [
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    "Bringing Network Coding into Multi-Robot Systems",
    "AC-RLNC Paper"
   ]
  },
  "AST_0024350e": {
   "name": "Network Coding MRS Simulation Framework",
   "type": "framework",
   "source": "https://github.com/AnilZaher/network-coding-mrs",
   "aliases": [
    "network-coding-mrs",
    "AnilZaher NC MRS",
    "AC-RLNC Simulation"
   ]
  },
  "AST_fbf6a87a": {
   "name": "CBMF (arXiv:1308.2923)",
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   "source": "https://arxiv.org/abs/1308.2923",
   "aliases": [
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    "Backpressure Message Ferrying"
   ]
  },
  "AST_c0b113b5": {
   "name": "Message Ferrying (WDTN 2004)",
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   "source": "https://doi.org/10.1145/989459.989488",
   "aliases": [
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    "FIMF",
    "NIMF"
   ]
  },
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   "name": "SuperLoc",
   "type": "tool",
   "source": "https://github.com/superxslam/SuperOdom",
   "aliases": [
    "SuperLoc",
    "SuperOdom Localization",
    "Predictive Alignment Risk Localization"
   ]
  },
  "AST_7c5f7852": {
   "name": "Vapor",
   "type": "package",
   "source": "https://github.com/efreidun/vapor",
   "aliases": [
    "Vapor",
    "Variational Pose Regression",
    "efreidun/vapor"
   ]
  },
  "AST_a7ce35dd": {
   "name": "ric_loc",
   "type": "package",
   "source": "https://github.com/SNU-DLLAB/ric_loc",
   "aliases": [
    "RIC-Loc",
    "ric_loc",
    "Reference-Induced Consensus",
    "SNU-DLLAB/ric_loc"
   ]
  },
  "AST_7590a799": {
   "name": "VGGT",
   "type": "model",
   "source": "https://github.com/facebookresearch/vggt",
   "aliases": [
    "Visual Geometry Grounded Transformer",
    "facebookresearch/vggt",
    "VGGT-1B"
   ]
  },
  "AST_3f35eeca": {
   "name": "AmbiguousReloc",
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   "source": "https://github.com/efreidun/vapor",
   "aliases": [
    "AmbiguousReloc Dataset",
    "Ambiguous Relocalization"
   ]
  },
  "AST_1bd1b61c": {
   "name": "Simscape Multibody",
   "type": "simulator",
   "source": "https://www.mathworks.com/products/simscape-multibody.html",
   "aliases": [
    "SimMechanics"
   ]
  },
  "AST_30305851": {
   "name": "RAVEN-II",
   "type": "robot",
   "source": "https://github.com/uw-biorobotics/raven2",
   "aliases": [
    "RAVEN-II Surgical Robot"
   ]
  },
  "AST_a4e657a0": {
   "name": "RCM-PC Cube",
   "type": "simulator",
   "source": "https://rcmpc-cube.github.io",
   "aliases": [
    "RCM-PC"
   ]
  },
  "AST_e3b18074": {
   "name": "iTracker",
   "type": "model",
   "source": "https://github.com/CSAILVision/GazeCapture",
   "aliases": [
    "Eye Tracking for Everyone",
    "GazeCapture iTracker"
   ]
  },
  "AST_506032b3": {
   "name": "WebGazer.js",
   "type": "framework",
   "source": "https://github.com/brownhci/WebGazer",
   "aliases": [
    "WebGazer",
    "WebGazer.js",
    "Brown HCI WebGazer"
   ]
  },
  "AST_9d23ca7d": {
   "name": "ptgaze",
   "type": "package",
   "source": "https://pypi.org/project/ptgaze/",
   "aliases": [
    "ptgaze",
    "pytorch_mpiigaze_demo"
   ]
  },
  "AST_de77187b": {
   "name": "FAZE (Few-Shot Adaptive Gaze Estimation)",
   "type": "model",
   "source": "https://github.com/NVlabs/few_shot_gaze",
   "aliases": [
    "Few-Shot Gaze",
    "FAZE Framework",
    "NVlabs few_shot_gaze"
   ]
  },
  "AST_18d0b5a8": {
   "name": "Tri-Cam",
   "type": "framework",
   "source": "https://arxiv.org/abs/2409.19554",
   "aliases": [
    "Tri-Cam Gaze Tracking",
    "Triple Camera Gaze System",
    "Tri-Cam Camera Network"
   ]
  },
  "AST_87d64436": {
   "name": "EYEDIAP",
   "type": "dataset",
   "source": "https://zenodo.org/record/4467455",
   "aliases": [
    "EYEDIAP Dataset",
    "Idiap RGB-D Gaze Dataset"
   ]
  },
  "AST_8b3bcdcd": {
   "name": "Smart Eye Aurora / Pro",
   "type": "framework",
   "source": "https://www.smarteye.se/solutions/products/",
   "aliases": [
    "Smart Eye Pro",
    "Smart Eye Aurora",
    "Smart Eye AI-X",
    "SmartEye Pro"
   ]
  },
  "AST_07323e26": {
   "name": "EMQX Cloud",
   "type": "framework",
   "source": "https://www.emqx.com/en/cloud",
   "aliases": [
    "EMQX Cloud MQTT Broker"
   ]
  },
  "AST_a2f0e65c": {
   "name": "RA-DP",
   "type": "tool",
   "source": "https://arxiv.org/abs/2503.04051",
   "aliases": [
    "Rapid Adaptive Diffusion Policy",
    "RA-DiffusionPolicy"
   ]
  },
  "AST_5f7a6b05": {
   "name": "AdaReP",
   "type": "tool",
   "source": "https://arxiv.org/abs/2606.23079",
   "aliases": [
    "Adaptive Replanning",
    "AdaReP wrapper"
   ]
  },
  "AST_98a12294": {
   "name": "When to Replan (ICRA 2024)",
   "type": "paper",
   "source": "https://arxiv.org/abs/2304.12046",
   "aliases": [
    "When to Replan?",
    "DRL Replanning Strategy (ICRA 2024)"
   ]
  },
  "AST_f3e84371": {
   "name": "nav2_planner",
   "type": "ros_package",
   "source": "https://github.com/ros-navigation/navigation2/tree/main/nav2_planner",
   "aliases": []
  },
  "AST_1ba91a5a": {
   "name": "Grounded SAM 2",
   "type": "framework",
   "source": "https://github.com/IDEA-Research/Grounded-SAM-2",
   "aliases": [
    "Grounded-SAM-2",
    "IDEA-Research Grounded SAM 2"
   ]
  },
  "AST_01532740": {
   "name": "ClearML",
   "type": "tool",
   "source": "https://github.com/allegroai/clearml",
   "aliases": [
    "ClearML MLOps",
    "Allegro Trains"
   ]
  },
  "AST_62e08590": {
   "name": "MIRRER Framework",
   "type": "paper",
   "source": "https://arxiv.org/abs/2408.04736",
   "aliases": [
    "MIRRER",
    "Multiple Iterated Reproduced Replicated Experiments with Robots"
   ]
  },
  "AST_ce24270c": {
   "name": "conda-lock",
   "type": "tool",
   "source": "https://github.com/conda/conda-lock",
   "aliases": [
    "conda lock file",
    "conda-lock"
   ]
  },
  "AST_85b63535": {
   "name": "GNU Guix",
   "type": "tool",
   "source": "https://git.savannah.gnu.org/cgit/guix.git",
   "aliases": [
    "Guix",
    "GNU Guix System"
   ]
  },
  "AST_c159d5ba": {
   "name": "ReproZip",
   "type": "tool",
   "source": "https://github.com/VIDA-NYU/reprozip",
   "aliases": [
    "ReproZip Tool",
    "reprozip"
   ]
  },
  "AST_50a6ac3f": {
   "name": "Popper",
   "type": "tool",
   "source": "https://github.com/getpopper/popper",
   "aliases": [
    "Popper CLI",
    "Popper Convention Tool"
   ]
  },
  "AST_c8a7a351": {
   "name": "Code Ocean",
   "type": "tool",
   "source": "https://codeocean.com",
   "aliases": [
    "Code Ocean Platform",
    "Compute Capsule"
   ]
  },
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   "name": "GitHub Actions",
   "type": "tool",
   "source": "https://github.com/features/actions",
   "aliases": [
    "GitHub Actions CI",
    "GH Actions"
   ]
  },
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   "type": "tool",
   "source": "https://github.com/ethanhirschowitz/warp-rl",
   "aliases": []
  },
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   "name": "ARPO Racing",
   "type": "tool",
   "source": "https://github.com/raphajaner/arpo_racing",
   "aliases": [
    "alpha-RPO"
   ]
  },
  "AST_9ad2da50": {
   "name": "ISO 14971:2019 Medical Devices -- Application of risk management to medical devices",
   "type": "tool",
   "source": "https://www.iso.org/standard/72704.html",
   "aliases": [
    "ISO 14971",
    "医疗器械风险管理标准",
    "EN ISO 14971"
   ]
  },
  "AST_8feb06e9": {
   "name": "FiMDP",
   "type": "package",
   "source": "https://github.com/FiMDP/FiMDP",
   "aliases": [
    "Fuel in Markov Decision Processes",
    "FiMDP Package",
    "ConsMDP Python"
   ]
  },
  "AST_1f5218be": {
   "name": "FiMDPEnv",
   "type": "simulator",
   "source": "https://github.com/FiMDP/FiMDPEnv",
   "aliases": [
    "FiMDP Environments",
    "fimdpenv"
   ]
  },
  "AST_36faa946": {
   "name": "LTLf2DFA",
   "type": "tool",
   "source": "https://github.com/whitemech/LTLf2DFA",
   "aliases": [
    "ltlf2dfa",
    "LTLf to DFA"
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  },
  "AST_7ec89177": {
   "name": "MONA",
   "type": "tool",
   "source": "https://www.brics.dk/mona/",
   "aliases": [
    "MONA tool",
    "MONA DFA",
    "brics mona"
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   "source": "https://arxiv.org/abs/2605.16932",
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    "BAT-Nav",
    "Budget-Aware Arbitration and Termination"
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  },
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   "source": "https://arxiv.org/abs/2605.16932v1",
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    "MORN",
    "Metacognitive Object-Goal Regulation Navigation"
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   "source": "https://arxiv.org/abs/2509.25556",
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    "ESL",
    "Exhaustive-Serve-Longest"
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  },
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   "source": "https://arxiv.org/abs/2606.16972",
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    "Regret-Guided Update Scheduling",
    "Skip-Update Scheduling"
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   "source": "https://arxiv.org/abs/2604.02142",
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    "PRO-SPECT",
    "Probabilistically Safe Scalable Planning for Energy-Aware Coordinated UAV-UGV Teams"
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   "source": "https://arxiv.org/abs/1204.1909",
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    "KUBE",
    "Knapsack Based Optimal Policies for Budget-Limited Multi-Armed Bandits",
    "Budget-Limited MAB"
   ]
  },
  "AST_d9d33340": {
   "name": "VRPy",
   "type": "package",
   "source": "https://github.com/Kuifje02/vrpy",
   "aliases": [
    "Vehicle Routing Problem Python"
   ]
  },
  "AST_46894689": {
   "name": "op-solver",
   "type": "package",
   "source": "https://github.com/gkobeaga/op-solver",
   "aliases": [
    "Orienteering Problem Solver"
   ]
  },
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   "name": "Attention Model for Routing Problems",
   "type": "package",
   "source": "https://github.com/wouterkool/attention-learn-to-route",
   "aliases": [
    "Attention Routing Solver",
    "Kool et al. 2019 Attention Model"
   ]
  },
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   "type": "tool",
   "source": "https://ojs.aaai.org/index.php/AAAI/article/view/9484",
   "aliases": []
  },
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   "name": "PSPLIB",
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   "source": "https://www.om-db.wi.tum.de/psplib/",
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  },
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   "name": "CPN Tools",
   "type": "framework",
   "source": "http://cpntools.org",
   "aliases": [
    "CPN-Tools"
   ]
  },
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   "source": "http://www.tapaal.net",
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  },
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   "type": "tool",
   "source": "https://arxiv.org/abs/2607.00591v2",
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   "source": "https://openreview.net/forum?id=TVI3OXeKuP",
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   "source": "https://openreview.net/forum?id=ZRGZ4OcfXV",
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  },
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   "source": "https://github.com/SINTEF/paraspace",
   "aliases": [
    "pyparaspace",
    "SINTEF paraspace"
   ]
  },
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   "name": "NDDL (New Domain Description Language)",
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   "source": "https://github.com/nasa/europa",
   "aliases": [
    "New Domain Description Language",
    "NDDL language"
   ]
  },
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   "name": "DCGM Exporter",
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   "source": "https://github.com/NVIDIA/dcgm-exporter",
   "aliases": [
    "NVIDIA DCGM Exporter",
    "dcgm-exporter"
   ]
  },
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   "source": "https://arxiv.org/abs/2606.19632",
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    "Farooq DT Distillation Verification",
    "PRISM DT Verification"
   ]
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   "aliases": [
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    "MixtureOfAgentsPack"
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  },
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   "source": "https://github.com/xiutian/GEDI",
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    "xiutian/GEDI",
    "GEDI Electoral Voting"
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  },
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   "aliases": [
    "mingju-c/AMapReduce",
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  },
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   "aliases": [
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    "LLM MapReduce"
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   "source": "https://docs.cohere.com/reference/rerank-1",
   "aliases": [
    "Cohere Rerank",
    "Cohere Rerank 4 Pro"
   ]
  },
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   "aliases": [
    "LangChain CrossEncoderReranker",
    "ContextualCompressionRetriever reranker"
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   "source": "https://github.com/castorini/rank_llm",
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    "rank_llm",
    "RankGPT",
    "MonoT5",
    "DuoT5"
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   "source": "https://docs.llamaindex.ai",
   "aliases": [
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    "LlamaIndex RankGPT"
   ]
  },
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   "source": "https://python.langchain.com",
   "aliases": [
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    "LangChain listwise rerank"
   ]
  },
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   "source": "https://docs.haystack.deepset.ai",
   "aliases": [
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    "Haystack ColBERT reranker"
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    "Qdrant MAX_SIM"
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    "optuna",
    "TPE Optimizer"
   ]
  },
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   "source": "https://github.com/run-llama/llama_index",
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    "ParamTuner",
    "RayTuneParamTuner",
    "llama_index param_tuner"
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  },
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   "source": "[待核查]",
   "aliases": [
    "RAISE",
    "RAG Architecture Search"
   ]
  },
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   "name": "Retriever Portfolios",
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   "source": "[待核查]",
   "aliases": [
    "Retriever Portfolios",
    "Best-of-k Retriever"
   ]
  },
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    "zyc140345/HARR"
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  },
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    "Retrieval Preference Optimization"
   ]
  },
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   "aliases": [
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    "vendi-score",
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    "Diversity-Quality Tradeoff RAG"
   ]
  },
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    "lasgroup rewarduq",
    "Uncertainty-Aware Reward Model"
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  },
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   "source": "https://github.com/google-deepmind/ai-safety-gridworlds",
   "aliases": [
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    "deepmind gridworlds",
    "safety gridworld"
   ]
  },
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   "source": "https://github.com/hiwonjoon/ICML2019-TREX",
   "aliases": [
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    "T-REX PyTorch"
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  },
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   "source": "https://github.com/dsbrown1331/CoRL2019-DREX",
   "aliases": [
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    "D-REX code",
    "Disturbance-based Reward Extrapolation code"
   ]
  },
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   "source": "https://sites.google.com/view/bayesianrex/",
   "aliases": [
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    "B-REX code"
   ]
  },
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   "name": "IRLEED",
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   "source": "https://github.com/mbeliaev1/IRLEED",
   "aliases": [
    "IRLEED Code",
    "mbeliaev1/IRLEED"
   ]
  },
  "AST_05441f14": {
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   "source": "https://github.com/Div99/IQ-Learn",
   "aliases": [
    "IQ-Learn Code",
    "Div99/IQ-Learn",
    "Div-Infinity/IQ-Learn"
   ]
  },
  "AST_632ec91e": {
   "name": "Feasible Reward Set Approach (Kim et al. 2026)",
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   "source": "https://arxiv.org/abs/2605.30903",
   "aliases": [
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    "Kim et al. 2026",
    "arXiv:2605.30903"
   ]
  },
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   "aliases": [
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    "PyTorch SAC"
   ]
  },
  "AST_89cae55f": {
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   "source": "https://github.com/NVlabs/GDPO",
   "aliases": [
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    "Group reward-Decoupled Normalization Policy Optimization"
   ]
  },
  "AST_c9bdb940": {
   "name": "SASR",
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   "source": "https://github.com/mahaozhe/SASR",
   "aliases": [
    "Self-Adaptive Success Rate Reward Shaping",
    "mahaozhe/SASR"
   ]
  },
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   "source": "https://github.com/luigiberducci/auto-shaping",
   "aliases": [
    "luigiberducci/auto-shaping",
    "auto_shaping",
    "Berducci auto-shaping library"
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  },
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   "source": "https://f1tenth.org",
   "aliases": [
    "F1TENTH Autonomous Racing Platform",
    "f1tenth_gym",
    "F1-Tenth"
   ]
  },
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   "source": "https://github.com/sllurp/sllurp",
   "aliases": [
    "sllurp LLRP library",
    "sllurp/sllurp"
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  },
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   "source": "https://github.com/MISTLab/VIR-SLAM",
   "aliases": [
    "VIR-SLAM",
    "MISTLab VIR-SLAM"
   ]
  },
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   "source": "https://github.com/NVlabs/PoseRBPF",
   "aliases": [
    "PoseRBPF",
    "Rao-Blackwellized Particle Filter Pose Tracking"
   ]
  },
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   "name": "YCBInEOAT",
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   "source": "https://github.com/wenbowen123/iros20-6d-pose-tracking",
   "aliases": [
    "YCBInEOAT",
    "YCB In End-Of-Arm-Tool"
   ]
  },
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   "source": "https://github.com/pydy/pydy",
   "aliases": [
    "PyDy",
    "Python Dynamics",
    "pydy"
   ]
  },
  "AST_f7aaafa8": {
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   "source": "https://github.com/gtrll/multi-robot-rmpflow",
   "aliases": [
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    "gtrll multi-robot-rmpflow"
   ]
  },
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   "source": "https://openi.cn/292026.html",
   "aliases": [
    "GraspVLA",
    "银河通用 GraspVLA"
   ]
  },
  "AST_6361b062": {
   "name": "ISO/TR 24971 Medical Device Risk Guidance",
   "type": "tool",
   "source": "https://www.iso.org/standard/72705.html",
   "aliases": [
    "ISO/TR 24971",
    "ISO TR 24971"
   ]
  },
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   "name": "ISO/TS 15066 Collaborative Robots",
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   "source": "https://www.iso.org/standard/62996.html",
   "aliases": []
  },
  "AST_8af3d090": {
   "name": "ISO 3864-2 Product Safety Label Standard",
   "type": "tool",
   "source": "https://www.iso.org/standard/62458.html",
   "aliases": [
    "ISO 3864-2",
    "Label Standard"
   ]
  },
  "AST_8c40f4ca": {
   "name": "ISO 7010 Registered Safety Signs",
   "type": "tool",
   "source": "https://www.iso.org/standard/62458.html",
   "aliases": [
    "ISO 7010",
    "Safety Signs"
   ]
  },
  "AST_bd2ccc2f": {
   "name": "ISO 20607 Instruction Handbook Standard",
   "type": "tool",
   "source": "https://www.iso.org/standard/68485.html",
   "aliases": [
    "ISO 20607",
    "Instruction Handbook"
   ]
  },
  "AST_334f9fe6": {
   "name": "ANSI Z535 Safety Sign Standard",
   "type": "tool",
   "source": "https://www.nema.org/standards",
   "aliases": [
    "ANSI Z535",
    "North American Safety"
   ]
  },
  "AST_be5db4c1": {
   "name": "IEC 82079-1 Information for Use Standard",
   "type": "tool",
   "source": "https://webstore.iec.ch/",
   "aliases": [
    "IEC 82079-1",
    "Information for Use"
   ]
  },
  "AST_b417923d": {
   "name": "Risk-Sensitive Reinforcement Learning via Policy Gradient Search",
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   "source": "https://www.jmlr.org/papers/v16/tamar15a.html",
   "aliases": [
    "Tamar 2015 Risk-Sensitive RL",
    "Risk-Sensitive RL"
   ]
  },
  "AST_ab680956": {
   "name": "continuous_risk_map",
   "type": "tool",
   "source": "https://github.com/ethz-asl/continuous_risk_map",
   "aliases": [
    "Continuous Risk Map",
    "ETH ASL continuous risk map"
   ]
  },
  "AST_1431c952": {
   "name": "RiskSensitiveMPC",
   "type": "tool",
   "source": "https://github.com/StanfordASL/RiskSensitiveMPC",
   "aliases": [
    "StanfordASL RiskSensitiveMPC",
    "CVaR MPPI"
   ]
  },
  "AST_79f07427": {
   "name": "Risk-Averse Model Predictive Control",
   "type": "paper",
   "source": "https://arxiv.org/abs/2109.13601",
   "aliases": [
    "Risk-Averse MPC",
    "Hakobyan CVaR MPPI"
   ]
  },
  "AST_5c0ec9db": {
   "name": "Distributionally Robust Policy Learning via Adversarial Environment Generation",
   "type": "paper",
   "source": "https://arxiv.org/abs/2201.01393",
   "aliases": [
    "DRO Policy Learning",
    "Adversarial Environment Generation"
   ]
  },
  "AST_d77e7d76": {
   "name": "Distributionally Robust Policy Learning for Safe Navigation in Crowded Environments",
   "type": "paper",
   "source": "https://arxiv.org/abs/2209.12345",
   "aliases": [
    "DRO Crowd Nav",
    "Safe Navigation Crowded Environments"
   ]
  },
  "AST_63882642": {
   "name": "DSAC-v2",
   "type": "framework",
   "source": "https://github.com/Jingliang-Duan/DSAC-v2",
   "aliases": [
    "Distributional SAC v2",
    "DSAC-T"
   ]
  },
  "AST_faf69172": {
   "name": "GOPS",
   "type": "framework",
   "source": "https://github.com/Intelligent-Driving-Laboratory/GOPS",
   "aliases": [
    "GOPS",
    "General Optimal control Problem Solver",
    "Intelligent-Driving-Laboratory/GOPS"
   ]
  },
  "AST_d7d22724": {
   "name": "Bradley-Terry Model (1952)",
   "type": "framework",
   "source": "https://www.jstor.org/stable/2334029",
   "aliases": [
    "Bradley-Terry 1952",
    "BT Model",
    "Paired Comparison Model"
   ]
  },
  "AST_ec90ea00": {
   "name": "GRAPE",
   "type": "framework",
   "source": "https://github.com/aiming-lab/GRAPE",
   "aliases": [
    "GRAPE Preference Alignment",
    "Guided-Reinforced VLA Preference Optimization",
    "aiming-lab GRAPE"
   ]
  },
  "AST_2294ef5c": {
   "name": "SimpleVLA-RL",
   "type": "package",
   "source": "https://github.com/PRIME-RL/SimpleVLA-RL",
   "aliases": [
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    "SimpleVLA-RL Framework",
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    "bully-algorithm"
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    "全纯滚动球"
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  },
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    "OpenCascade Technology",
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    "Peterson Kt Charts"
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  },
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  },
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    "Blue Robotics T200",
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  },
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    "Kongsberg K-Pos"
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    "DeepTrekker Revolution BRIDGE"
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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  },
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   "aliases": []
  },
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   "source": "https://www.iso.org/standard/62996.html",
   "aliases": []
  },
  "AST_8e455503": {
   "name": "ISO 21448 Road Vehicles SOTIF",
   "type": "tool",
   "source": "https://www.iso.org/standard/77490.html",
   "aliases": []
  },
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   "source": "https://github.com/LouisJouret/Neural-Control-Invariance-Checker",
   "aliases": [
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    "set invariance checker",
    "LouisJouret/Neural-Control-Invariance-Checker"
   ]
  },
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    "dL",
    "differential dynamic logic",
    "Platzer dL"
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  },
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   "name": "ISSA/SSA Safe Guard",
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   "source": "https://arxiv.org/abs/2405.02754",
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    "Implicit Safe Set Algorithm",
    "ISSA",
    "Safe Set Algorithm"
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  },
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   "source": "https://github.com/PKU-Alignment/SafeDreamer",
   "aliases": [
    "PKU-Alignment/SafeDreamer",
    "Safe RL World Model",
    "SafeDreamer"
   ]
  },
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   "type": "framework",
   "source": "arXiv:2510.14959 (Caltech)",
   "aliases": [
    "SHIELD",
    "Caltech SHIELD",
    "Hierarchical CBF Safety Layer"
   ]
  },
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   "name": "CMU-IntentLab/UNISafe",
   "type": "package",
   "source": "https://github.com/CMU-IntentLab/UNISafe",
   "aliases": [
    "UNISafe Code",
    "Uncertainty-aware Latent Safety Filter Implementation"
   ]
  },
  "AST_4db3dc33": {
   "name": "SAFER-Splat",
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   "source": "https://github.com/chengine/safer-splat",
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   "aliases": [
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   "source": "https://www.robotis.com/OP3",
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    "Robotis OP3"
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    "roberta-base-go_emotions",
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   "type": "framework",
   "source": "https://github.com/Sreyan88/MMER",
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    "MMER",
    "Multimodal Multi-task SER",
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  },
  "AST_23794f2a": {
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   "type": "package",
   "source": "https://github.com/jitsi/jiwer",
   "aliases": [
    "jiwer",
    "WER Calculation",
    "Speech Recognition Error Rate"
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  },
  "AST_a454e832": {
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   "type": "model",
   "source": "https://github.com/QwenLM/Qwen-Audio",
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    "Qwen-Audio",
    "Qwen-Audio-Chat",
    "QwenLM/Qwen-Audio"
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   "type": "model",
   "source": "https://github.com/QwenLM/Qwen2-Audio",
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    "Qwen2-Audio",
    "Qwen2-Audio-7B",
    "Qwen2-Audio-7B-Instruct"
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   "type": "model",
   "source": "https://github.com/bytedance/SALMONN",
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    "SALMONN",
    "SALMONN-7B",
    "SALMONN-13B"
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  },
  "AST_d32f5b03": {
   "name": "VoiceBank-DEMAND",
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   "source": "https://datashare.ed.ac.uk/handle/10283/2791",
   "aliases": [
    "Valentini-DEMAND",
    "Noisy Speech Database for Training Speech Enhancement"
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  },
  "AST_3a469ab1": {
   "name": "pesq",
   "type": "package",
   "source": "https://github.com/ludlows/PESQ",
   "aliases": [
    "python-pesq",
    "ludlows PESQ"
   ]
  },
  "AST_0d040936": {
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   "type": "package",
   "source": "https://github.com/mpariente/pystoi",
   "aliases": [
    "python-stoi"
   ]
  },
  "AST_d4bb3ea3": {
   "name": "DNSMOS",
   "type": "framework",
   "source": "https://github.com/microsoft/DNS-Challenge",
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    "DNSMOS P.835",
    "Deep Noise Suppression MOS"
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  },
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   "name": "ITU-T G.107 E-model",
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   "source": "https://www.itu.int/rec/T-REC-G.107/en",
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    "E-model",
    "G.107"
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    "Impairment Factor Tables"
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   "source": "https://chromium.googlesource.com/external/webrtc/",
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    "WebRTC APM",
    "webrtc-audio-processing"
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  },
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   "name": "NISQA",
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   "source": "https://github.com/gabrielmittag/NISQA",
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    "Non-Intrusive Speech Quality Assessment"
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  },
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   "source": "https://github.com/gabrielmittag/NISQA/wiki/NISQA-Corpus",
   "aliases": [
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  },
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   "name": "mos-finetune-ssl",
   "type": "framework",
   "source": "https://github.com/nii-yamagishilab/mos-finetune-ssl",
   "aliases": [
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    "Wav2vec MOS Finetune"
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   "source": "https://zenodo.org/record/6572573",
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    "Blizzard Voice Conversion Challenge Corpus"
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   "source": "https://github.com/TaoRuijie/TalkNet-ASD",
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    "TalkSet ASD Dataset"
   ]
  },
  "AST_38294579": {
   "name": "Columbia ASD Dataset",
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   "source": "https://github.com/TaoRuijie/TalkNet-ASD",
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    "Columbia ASD"
   ]
  },
  "AST_3ef3aaec": {
   "name": "diart",
   "type": "package",
   "source": "https://github.com/juanmc2005/diart",
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    "diart streaming diarization"
   ]
  },
  "AST_58d4f72d": {
   "name": "pyannote.metrics",
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   "source": "https://github.com/pyannote/pyannote-metrics",
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    "pyannote-metrics",
    "pyannote metrics"
   ]
  },
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   "name": "SYNTHIA-AL",
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   "source": "http://synthia-dataset.net/downloads/",
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    "SYNTHIA AL",
    "Synthetic Driving Dataset"
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  },
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   "name": "SpiralSTC Plugin",
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   "source": "https://github.com/nobleo/full_coverage_path_planner/blob/master/src/SpiralSTC.cpp",
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  },
  "AST_d6716ff3": {
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   "source": "https://github.com/nobleo/full_coverage_path_planner/tree/master/nodes",
   "aliases": [
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  },
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   "source": "https://github.com/mrath/mobile_robot_simulator",
   "aliases": []
  },
  "AST_84bd3b6b": {
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   "aliases": [
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    "共形狭缝映射论文"
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  },
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   "name": "Schwarz-Christoffel Toolbox for MATLAB",
   "type": "tool",
   "source": "https://github.com/tobydriscoll/sc-toolbox",
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    "SC Toolbox",
    "Schwarz-Christoffel toolbox"
   ]
  },
  "AST_c99bf418": {
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   "source": "无公开仓库",
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   ]
  },
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   "name": "Girona 500 I-AUV",
   "type": "robot",
   "source": "https://cirs.udg.edu/infrastructure/robots/girona-i-auv/",
   "aliases": [
    "Girona I-AUV",
    "Girona500",
    "CIRS Girona 500"
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   "source": "https://journal.xidian.edu.cn/dzkj/CN/10.16180/j.cnki.issn1007-7820.2023.06.004",
   "aliases": [
    "Lu Liang 2023 Impedance Grasping",
    "水下机械手阻抗抓取"
   ]
  },
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   "name": "WaterLinked-Underwater-GPS-G2",
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   "source": "https://github.com/abubake/WaterLinked-Underwater-GPS-G2",
   "aliases": [
    "WaterLinked UGPS G2 client",
    "abubake UGPS"
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  },
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   "name": "sherpa-onnx KWS",
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   "source": "https://github.com/k2-fsa/sherpa-onnx",
   "aliases": [
    "k2-fsa/sherpa-onnx",
    "sherpa-onnx-kws"
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   "name": "FANUC PaintPro",
   "type": "tool",
   "source": "FANUC专有商业软件",
   "aliases": []
  },
  "AST_8383b3e7": {
   "name": "ABB IRC5P",
   "type": "robot",
   "source": "ABB专有硬件",
   "aliases": []
  },
  "AST_5cdaca05": {
   "name": "SROS2_CLI",
   "type": "tool",
   "source": "https://github.com/ros2/sros2",
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  },
  "AST_9f3ed1e2": {
   "name": "ros-swg/turtlebot3_demo",
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   "source": "https://github.com/ros-swg/turtlebot3_demo",
   "aliases": [
    "turtlebot3_demo",
    "Secure Turtlebot3 Demo",
    "rosswg/turtlebot3_demo"
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  },
  "AST_7151cce8": {
   "name": "Unified Visual-Tactile Manipulation (LQTS)",
   "type": "model",
   "source": "https://github.com/LQTS/unified-vt-manip",
   "aliases": [
    "unified-vt-manip",
    "LQTS unified-vt-manip"
   ]
  },
  "AST_b6620c39": {
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   "source": "https://github.com/allenai/molmo",
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    "Molmo VLM",
    "Molmo-7B"
   ]
  },
  "AST_1374d8c8": {
   "name": "foc-wheel-legged-robot",
   "type": "robot",
   "source": "https://github.com/Skythinker616/foc-wheel-legged-robot",
   "aliases": []
  },
  "AST_b151e30f": {
   "name": "legged_perceptive",
   "type": "framework",
   "source": "https://github.com/qiayuanl/legged_perceptive",
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  },
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   "source": "https://www.science.org/doi/10.1126/scirobotics.adz7397",
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  },
  "AST_b0602cf8": {
   "name": "ocs2_robotic_assets",
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   "source": "https://github.com/leggedrobotics/ocs2_robotic_assets",
   "aliases": []
  },
  "AST_5bb6d82f": {
   "name": "Sleiman et al. Unified MPC Framework for Whole-Body Dynamic Locomotion",
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   "source": "https://doi.org/10.1109/LRA.2021.3068908",
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  },
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   "source": "https://doi.org/10.1109/IROS55540.2023.10341442",
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  },
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   "source": "https://arxiv.org/abs/2404.05695",
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  },
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   "source": "https://arxiv.org/abs/2109.11978",
   "aliases": []
  },
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   "source": "https://arxiv.org/abs/2509.10771",
   "aliases": []
  },
  "AST_f49f0518": {
   "name": "RoboCup@Home RuleBook",
   "type": "tool",
   "source": "https://github.com/RoboCupAtHome/RuleBook",
   "aliases": []
  },
  "AST_8831e4bf": {
   "name": "WRS Assembly Challenge Task Board Specification",
   "type": "tool",
   "source": "[待核查]",
   "aliases": []
  },
  "AST_264a743e": {
   "name": "Deep Bisimulation for Control",
   "type": "framework",
   "source": "https://github.com/facebookresearch/deep_bisim4control",
   "aliases": [
    "Deep Bisim for Control"
   ]
  },
  "AST_fa96ff82": {
   "name": "CRIU",
   "type": "tool",
   "source": "https://github.com/checkpoint-restore/criu",
   "aliases": [
    "Checkpoint/Restore In Userspace",
    "criu",
    "CRIU tool"
   ]
  },
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   "name": "llm-reasoners",
   "type": "package",
   "source": "https://github.com/maitrix-org/llm-reasoners",
   "aliases": [
    "LLM Reasoners",
    "maitrix-org/llm-reasoners",
    "llm-reasoners library"
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  },
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   "name": "Madagascar (SAT Planning System)",
   "type": "tool",
   "source": "http://users.ics.aalto.fi/rintanen/sat/",
   "aliases": [
    "Madagascar",
    "Madagascar-pC"
   ]
  },
  "AST_f7a75c63": {
   "name": "SATPLAN (Planning as Satisfiability)",
   "type": "tool",
   "source": "https://www.fast-downward.org (相关参考); SATPLAN 源码未获取稳定开源 URL",
   "aliases": [
    "Satplan",
    "SATPLAN2006",
    "SATPLAN04"
   ]
  },
  "AST_736a141c": {
   "name": "Kaggle ASL Alphabet Dataset",
   "type": "dataset",
   "source": "https://www.kaggle.com/datasets/grassknoted/asl-alphabet",
   "aliases": [
    "ASL Alphabet",
    "asl-alphabet",
    "American Sign Language Alphabet"
   ]
  },
  "AST_95113201": {
   "name": "Triesch/Marcel Hand Posture Datasets",
   "type": "dataset",
   "source": "http://www.idiap.ch/resource/gestures/",
   "aliases": [
    "Triesch hand posture",
    "Marcel hand posture",
    "IDIAP gesture dataset"
   ]
  },
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   "source": "https://universe.roboflow.com/lebanese-university/hand-gesture-recognition-object-detection",
   "aliases": [
    "Roboflow hand gesture",
    "hand-gesture-recognition-object-detection"
   ]
  },
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   "name": "torchvision ResNet18 ImageNet Pretrained Weights",
   "type": "model",
   "source": "https://download.pytorch.org/models/resnet18-f37072fd.pth",
   "aliases": [
    "ResNet18 ImageNet weights",
    "torchvision ResNet18",
    "resnet18-f37072fd",
    "IMAGENET1K_V1"
   ]
  },
  "AST_f4d1c757": {
   "name": "numb0824 wall-following-robot",
   "type": "package",
   "source": "https://github.com/numb0824/wall-following-robot",
   "aliases": [
    "numb0824 wall following",
    "PD wall following robot"
   ]
  },
  "AST_6d60cb47": {
   "name": "LIBELAS",
   "type": "tool",
   "source": "https://cvlibs.net/software/libelas/",
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    "Efficient Large-Scale Stereo Matching"
   ]
  },
  "AST_c852e4cd": {
   "name": "PSMNet",
   "type": "model",
   "source": "https://github.com/JiaRenChang/PSMNet",
   "aliases": [
    "Pyramid Stereo Matching Network"
   ]
  },
  "AST_b0c53947": {
   "name": "GA-Net",
   "type": "model",
   "source": "https://github.com/feihuzhang/GANet",
   "aliases": [
    "Guided Aggregation Net"
   ]
  },
  "AST_38abce73": {
   "name": "IGEV-Stereo",
   "type": "model",
   "source": "https://github.com/gangweiX/IGEV",
   "aliases": [
    "Iterative Geometry Encoding Volume for Stereo Matching"
   ]
  },
  "AST_918ab121": {
   "name": "Layer Jamming Continuum Manipulator",
   "type": "tool",
   "source": "Kim et al. 2013, IEEE TBME; Li et al. 2017, IEEE RAL",
   "aliases": [
    "Layer Jamming Manipulator",
    "Sheet Jamming Arm"
   ]
  },
  "AST_ec0299f7": {
   "name": "Fiber Jamming Manipulator",
   "type": "tool",
   "source": "Cianchetti et al. 2019, Frontiers in Robotics and AI 6:12",
   "aliases": [
    "Fiber Jamming Arm",
    "Filament Jamming Manipulator"
   ]
  },
  "AST_eeefe6ae": {
   "name": "moveit/stomp_moveit (archived ROS 1 plugin)",
   "type": "ros_package",
   "source": "https://github.com/moveit/stomp_moveit",
   "aliases": [
    "stomp_moveit",
    "moveit stomp_moveit",
    "ROS 1 STOMP plugin",
    "archived stomp_moveit"
   ]
  },
  "AST_30c9ba12": {
   "name": "network-slimming",
   "type": "package",
   "source": "https://github.com/Eric-mingjie/network-slimming",
   "aliases": [
    "Eric-mingjie/network-slimming",
    "Network Slimming PyTorch"
   ]
  },
  "AST_f9a1cad7": {
   "name": "PyTorch torch.nn.utils.prune",
   "type": "tool",
   "source": "https://pytorch.org/docs/stable/generated/torch.nn.utils.prune.html",
   "aliases": [
    "torch.nn.utils.prune",
    "PyTorch pruning",
    "torch prune"
   ]
  },
  "AST_f46c5b8a": {
   "name": "channel-pruning",
   "type": "package",
   "source": "https://github.com/yihui-he/channel-pruning",
   "aliases": [
    "yihui-he/channel-pruning",
    "ethanhe42/channel-pruning",
    "CP ICCV 2017"
   ]
  },
  "AST_ec0d04a3": {
   "name": "ThiNet",
   "type": "package",
   "source": "https://github.com/Rolf920/ThiNet",
   "aliases": [
    "Rolf920/ThiNet",
    "ThiNet LAMDA"
   ]
  },
  "AST_9bdbc7f1": {
   "name": "Torch-Pruning",
   "type": "framework",
   "source": "https://github.com/VainF/Torch-Pruning",
   "aliases": [
    "VainF/Torch-Pruning",
    "torch-pruning",
    "tp DepGraph framework"
   ]
  },
  "AST_58297d9c": {
   "name": "LLM-Pruner",
   "type": "package",
   "source": "https://github.com/horseee/LLM-Pruner",
   "aliases": [
    "horseee/LLM-Pruner",
    "LLM-Pruner NeurIPS 2023"
   ]
  },
  "AST_6cb3ca9e": {
   "name": "LLM-Shearing",
   "type": "package",
   "source": "https://github.com/princeton-nlp/LLM-Shearing",
   "aliases": [
    "princeton-nlp/LLM-Shearing",
    "Sheared LLaMA"
   ]
  },
  "AST_2b6a2d63": {
   "name": "GLOMAP",
   "type": "package",
   "source": "https://github.com/colmap/glomap",
   "aliases": [
    "Global Structure-from-Motion Revisited"
   ]
  },
  "AST_4de5c3dc": {
   "name": "TheiaSfM",
   "type": "package",
   "source": "https://github.com/sweeneychris/TheiaSfM",
   "aliases": [
    "Theia",
    "TheiaSfM library"
   ]
  },
  "AST_8b73a634": {
   "name": "HSfM CVPR 2017",
   "type": "paper",
   "source": "http://www.3dv.ac.cn/en/publication/cvpr-a/",
   "aliases": [
    "Hybrid Structure-from-Motion",
    "Cui CVPR 2017 HSfM"
   ]
  },
  "AST_9a4b761f": {
   "name": "VGGSfM",
   "type": "package",
   "source": "https://github.com/facebookresearch/vggsfm",
   "aliases": [
    "Visual Geometry Grounded Deep Structure From Motion"
   ]
  },
  "AST_b5a5a6e4": {
   "name": "VGGSfM v2.0.0 checkpoint",
   "type": "model",
   "source": "https://huggingface.co/facebook/VGGSfM/blob/main/vggsfm_v2_0_0.bin",
   "aliases": [
    "vggsfm_v2_0_0.bin",
    "VGGSfM pretrained model"
   ]
  },
  "AST_ada1cc1a": {
   "name": "CO3Dv2",
   "type": "dataset",
   "source": "https://github.com/facebookresearch/co3d",
   "aliases": [
    "CO3D v2",
    "Common Objects in 3D v2"
   ]
  },
  "AST_22712f3c": {
   "name": "OpenAI Function Calling API",
   "type": "framework",
   "source": "https://platform.openai.com/docs/guides/function-calling",
   "aliases": [
    "OpenAI Tool Calling",
    "OpenAI parallel function calling",
    "OpenAI Function Calling"
   ]
  },
  "AST_d2cd74ff": {
   "name": "DS-Agent",
   "type": "framework",
   "source": "https://github.com/guosyjlu/DS-Agent",
   "aliases": [
    "DS-Agent Framework",
    "Case-Based Reasoning Data Science Agent",
    "CBR-DS"
   ]
  },
  "AST_165ac1ab": {
   "name": "BAAI/llm-embedder",
   "type": "model",
   "source": "https://huggingface.co/BAAI/llm-embedder",
   "aliases": [
    "LLM-Embedder",
    "BAAI llm-embedder",
    "FlagEmbedding llm_embedder"
   ]
  },
  "AST_515a4d99": {
   "name": "OnRobot VGP20",
   "type": "robot",
   "source": "https://onrobot.com/en/products/vgp20-vacuum-gripper",
   "aliases": [
    "OnRobot VGP20",
    "VGP20 vacuum gripper"
   ]
  },
  "AST_4b2e4c97": {
   "name": "OnRobot VGC10 Compact Vacuum Gripper",
   "type": "robot",
   "source": "https://onrobot.com/en/products/vgc10-vacuum-gripper",
   "aliases": [
    "OnRobot VGC10",
    "VGC10 compact vacuum gripper"
   ]
  },
  "AST_efff8f71": {
   "name": "Schmalz FXCB",
   "type": "tool",
   "source": "https://www.schmalz.com/en/",
   "aliases": [
    "Schmalz FXCB",
    "FXCB palletizing gripper"
   ]
  },
  "AST_35e03f21": {
   "name": "Festo OVS Energy-Saving Valve",
   "type": "tool",
   "source": "https://www.festo.com/us/en/",
   "aliases": [
    "Festo OVS",
    "OVS energy-saving valve"
   ]
  },
  "AST_a7556ced": {
   "name": "SMC ZU07SA Vacuum Ejector",
   "type": "tool",
   "source": "[待核查] https://www.smcworld.com/",
   "aliases": [
    "SMC ZU07SA",
    "SMC 真空喷射器"
   ]
  },
  "AST_d91e39d9": {
   "name": "OnRobot D:PLOY",
   "type": "tool",
   "source": "[待核查] https://onrobot.com/en/products/d-ploy",
   "aliases": [
    "OnRobot D:PLOY",
    "D:PLOY 部署软件"
   ]
  },
  "AST_73c8c146": {
   "name": "OnRobot Compute Box",
   "type": "tool",
   "source": "[待核查] https://onrobot.com/en/products/vgp20-vacuum-gripper",
   "aliases": [
    "OnRobot Compute Box",
    "Compute Box"
   ]
  },
  "AST_2a00b751": {
   "name": "Schmalz Bellows Suction Cup",
   "type": "tool",
   "source": "https://www.kunag.com/index.php/new/index/g/c/id/3753.html",
   "aliases": [
    "Schmalz PSPF",
    "Schmalz 波纹吸盘"
   ]
  },
  "AST_0fe09673": {
   "name": "Piab Kenos Vacuum Gripper System",
   "type": "tool",
   "source": "https://m.11467.com/product/d8519051.htm",
   "aliases": [
    "Piab Kenos",
    "Kenos 真空抓具"
   ]
  },
  "AST_40f9ffe6": {
   "name": "Piab Kenos Configurator",
   "type": "tool",
   "source": "https://m.sohu.com/a/150944724_823251/",
   "aliases": [
    "Kenos Configurator",
    "Piab 配置器"
   ]
  },
  "AST_06a5d9df": {
   "name": "Orobica Bellows Suction Cup",
   "type": "tool",
   "source": "https://m.chem17.com/st210541/article_4268381.html",
   "aliases": [
    "Orobica Bellows",
    "Orobica 波纹吸盘"
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  },
  "AST_631faa01": {
   "name": "Dex-Net 3.0 Suction Grasp Dataset",
   "type": "dataset",
   "source": "https://berkeleyautomation.github.io/dex-net",
   "aliases": [
    "dexnet 3.0 dataset",
    "suction grasp dataset"
   ]
  },
  "AST_09c81808": {
   "name": "SuctionNet-1Billion Dataset",
   "type": "dataset",
   "source": "https://graspnet.net/datasets.html",
   "aliases": [
    "SuctionNet-1Billion",
    "suction grasp benchmark"
   ]
  },
  "AST_ec8fda8d": {
   "name": "SuctionNet-Baseline",
   "type": "tool",
   "source": "https://github.com/graspnet/suctionnet-baseline",
   "aliases": [
    "suctionnet-baseline",
    "SuctionNet baseline model"
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  },
  "AST_63fdc385": {
   "name": "suctionnetAPI",
   "type": "package",
   "source": "https://github.com/graspnet/suctionnetAPI",
   "aliases": [
    "suctionnetAPI",
    "suctionnet API"
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  },
  "AST_cf4e8677": {
   "name": "cdxgen",
   "type": "tool",
   "source": "https://github.com/CycloneDX/cdxgen",
   "aliases": []
  },
  "AST_19515ca7": {
   "name": "OSV-Scanner",
   "type": "tool",
   "source": "https://github.com/google/osv-scanner",
   "aliases": []
  },
  "AST_b15239db": {
   "name": "Intel RealSense Tracking Camera T265",
   "type": "tool",
   "source": "https://www.intelrealsense.com/tracking-camera-t265/",
   "aliases": [
    "RealSense T265",
    "Intel T265",
    "T265 Tracking Camera"
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  },
  "AST_24ebb738": {
   "name": "Intel RealSense LiDAR Camera L515",
   "type": "tool",
   "source": "https://www.intelrealsense.com/lidar-camera-l515/",
   "aliases": [
    "RealSense L515",
    "Intel L515",
    "L515 LiDAR Camera"
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  },
  "AST_54b02ae9": {
   "name": "T3",
   "type": "model",
   "source": "https://t3.alanz.info/",
   "aliases": [
    "T3",
    "Transferable Tactile Transformers"
   ]
  },
  "AST_f1378b86": {
   "name": "kth-ros-pkg/biotac_driver",
   "type": "ros_package",
   "source": "https://github.com/kth-ros-pkg/biotac_driver",
   "aliases": [
    "biotac_driver",
    "kth-ros-pkg biotac_driver",
    "BioTac ROS driver"
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  },
  "AST_404bc51f": {
   "name": "IanTheEngineer/Penn-haptics-bolt",
   "type": "ros_package",
   "source": "https://github.com/IanTheEngineer/Penn-haptics-bolt",
   "aliases": [
    "Penn-haptics-bolt",
    "UPenn BOLT biotac_stack",
    "Penn haptics biotac"
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  },
  "AST_cbfefb61": {
   "name": "TE Connectivity LDT0-028K PVDF 压电薄膜",
   "type": "robot",
   "source": "https://www.te.com/usa-en/product-CAT-PFS0003.html",
   "aliases": [
    "LDT0-028K",
    "TE Connectivity PVDF",
    "PVDF piezo film"
   ]
  },
  "AST_5982e50e": {
   "name": "VibroTact（Guo & Al, IEEE Sensors Letters 2024, 8(7)）",
   "type": "paper",
   "source": "https://ieeexplore.ieee.org/document/10574445",
   "aliases": [
    "VibroTact",
    "Guo 2024 Sensors Letters",
    "PVDF roughness sensing"
   ]
  },
  "AST_d0e0e596": {
   "name": "NeuroTac（Xu, Li, Ward-Cherrier, IROS 2025, arXiv:2509.14954）",
   "type": "paper",
   "source": "https://arxiv.org/abs/2509.14954",
   "aliases": [
    "NeuroTac",
    "Xu 2025 IROS",
    "neuromorphic tactile PVDF"
   ]
  },
  "AST_7c7528df": {
   "name": "NimbRo ANA Avatar XPRIZE（Pätzold et al., arXiv:2303.07186v3）",
   "type": "paper",
   "source": "https://arxiv.org/abs/2303.07186v3",
   "aliases": [
    "NimbRo ANA Avatar",
    "Pätzold 2023",
    "XPRIZE 2022 haptic"
   ]
  },
  "AST_f128fced": {
   "name": "八腿触觉传感器（Rodpongpun et al. 2015 UNSW 学术原型）",
   "type": "robot",
   "source": "https://ieeexplore.ieee.org/document/7319372",
   "aliases": [
    "eight-legged sensor",
    "Rodpongpun 2015 sensor",
    "contact-mechanics tactile sensor"
   ]
  },
  "AST_e3e782d7": {
   "name": "contactile/contactile_ros（Contactile ROS 1 driver）",
   "type": "ros_package",
   "source": "https://github.com/contactile/contactile_ros",
   "aliases": [
    "contactile_ros",
    "Contactile ROS driver"
   ]
  },
  "AST_1103fc3c": {
   "name": "Wu et al. 2024（滑敏软指尖，Measurement）",
   "type": "paper",
   "source": "https://www.sciencedirect.com/science/article/pii/S0263224124004493",
   "aliases": [
    "Wu 2024 Measurement",
    "slip-sensitive soft fingertip paper",
    "Wu 2024 滑敏光导软指尖（学术原型）",
    "Wu 2024 soft fingertip",
    "slip-sensitive light guide fingertip"
   ]
  },
  "AST_ff405c13": {
   "name": "Wei Chen et al. 2018 综述（IEEE Sensors Journal）",
   "type": "paper",
   "source": "https://ieeexplore.ieee.org/document/9777502",
   "aliases": [
    "Wei Chen 2018 review",
    "friction estimation review",
    "incipient slip detection review"
   ]
  },
  "AST_3084f966": {
   "name": "Back et al. 2014 接触感知指尖曲面跟随（ICRA）",
   "type": "paper",
   "source": "https://ieeexplore.ieee.org/document/6907434",
   "aliases": [
    "Back 2014 ICRA",
    "KCL contact sensing finger",
    "surface haptic exploration 2014"
   ]
  },
  "AST_c4f73d06": {
   "name": "Gwyddion",
   "type": "tool",
   "source": "https://gwyddion.net/",
   "aliases": [
    "Gwyddion SPM Analyzer"
   ]
  },
  "AST_280efea4": {
   "name": "pygwy",
   "type": "package",
   "source": "https://gwyddion.net/documentation/head/pygwy",
   "aliases": [
    "Gwyddion Python Bindings"
   ]
  },
  "AST_a7034f0d": {
   "name": "Zygo NewView 9000",
   "type": "tool",
   "source": "https://www.zygo.com/products/metrology-systems/3d-optical-profilers",
   "aliases": [
    "Zygo NewView 9000"
   ]
  },
  "AST_761ec258": {
   "name": "Bruker ContourSAIL",
   "type": "tool",
   "source": "https://www.bruker.com/en/products-and-solutions/metrology-and-inspection/3d-optical-metrology-systems",
   "aliases": [
    "Bruker ContourSAIL",
    "Bruker ContourX"
   ]
  },
  "AST_68b8c902": {
   "name": "Taylor Hobson Form Talysurf PGI Optics PRO",
   "type": "tool",
   "source": "https://www.taylor-hobson.com.cn/products/surface-profilers/optics-pgi",
   "aliases": [
    "Taylor Hobson PGI Optics PRO",
    "Form Talysurf PGI"
   ]
  },
  "AST_f943997c": {
   "name": "Mahr MarSurf LD 130 / LD 260",
   "type": "tool",
   "source": "https://www.mahr.com/",
   "aliases": [
    "Mahr MarSurf LD 130",
    "Mahr MarSurf LD 260"
   ]
  },
  "AST_25b578f9": {
   "name": "Jenoptik Hommel-Etamic W5 / W10 / T8000",
   "type": "tool",
   "source": "https://www.jenoptik.com/",
   "aliases": [
    "Hommel-Etamic W5",
    "Hommel-Etamic W10",
    "Hommel-Etamic T8000"
   ]
  },
  "AST_cde1a4e5": {
   "name": "Mitutoyo SJ-210 / SJ-410",
   "type": "tool",
   "source": "https://www.mitutoyo.com/",
   "aliases": [
    "Mitutoyo SJ-210",
    "Mitutoyo SJ-410",
    "Surftest SJ-210"
   ]
  },
  "AST_76c6e70f": {
   "name": "OptoSurf OS500",
   "type": "tool",
   "source": "https://www.optosurf.com/",
   "aliases": [
    "OptoSurf OS500",
    "OptoSurf scattered light sensor"
   ]
  },
  "AST_d2378103": {
   "name": "BYK wave-scan dual",
   "type": "tool",
   "source": "https://www.byk.com/",
   "aliases": [
    "BYK wave-scan dual",
    "BYK wave-scan"
   ]
  },
  "AST_2d05a36f": {
   "name": "BYK micro-TRI-gloss",
   "type": "tool",
   "source": "https://www.byk.com/",
   "aliases": [
    "BYK micro-TRI-gloss",
    "BYK TRI-gloss"
   ]
  },
  "AST_07f5f669": {
   "name": "Konica Minolta glossmeter",
   "type": "tool",
   "source": "https://www.konicaminolta.com/",
   "aliases": [
    "Konica Minolta glossmeter",
    "Konica Minolta multi-angle glossmeter"
   ]
  },
  "AST_0b89fe83": {
   "name": "KohYoung 3D AOI",
   "type": "tool",
   "source": "https://www.kohyoung.com/",
   "aliases": []
  },
  "AST_99332f2e": {
   "name": "Mirtec OmniVision 3D",
   "type": "tool",
   "source": "https://www.mirtec.com/",
   "aliases": []
  },
  "AST_70e08221": {
   "name": "3D SPI Equipment",
   "type": "tool",
   "source": "https://www.kohyoung.com/products",
   "aliases": []
  },
  "AST_2677a5e3": {
   "name": "BAD SLAM",
   "type": "tool",
   "source": "https://github.com/ETH3D/bad_slam",
   "aliases": [
    "BAD-SLAM",
    "bundle adjusted direct SLAM"
   ]
  },
  "AST_304afb3e": {
   "name": "SLICT",
   "type": "tool",
   "source": "https://github.com/brytsknguyen/slict",
   "aliases": [
    "SLICT2",
    "multi-scale surfel LiDAR-Inertial"
   ]
  },
  "AST_05da7d6b": {
   "name": "SurgRIPE",
   "type": "dataset",
   "source": "https://www.synapse.org/Synapse:syn51471789",
   "aliases": [
    "SurgRIPE",
    "SurgicalRIPE",
    "syn51471789"
   ]
  },
  "AST_47657847": {
   "name": "SurgiScan",
   "type": "tool",
   "source": "https://www.2dsurgical.com/",
   "aliases": [
    "SurgiScan Reader",
    "2DSurgical SurgiScan"
   ]
  },
  "AST_b24f00a2": {
   "name": "Efficient Surgical Tool Recognition via HMM",
   "type": "paper",
   "source": "https://hub.baai.ac.cn/paper/5dbd7981-df3a-48a7-bf4e-303b0e6fbc43",
   "aliases": [
    "HMM Tool Recognition",
    "HMM-Stabilized DL Surgical Tool"
   ]
  },
  "AST_1d9439fb": {
   "name": "奥比中光 Astra Pro",
   "type": "tool",
   "source": "https://www.orbbec.com/products/astra-pro/",
   "aliases": [
    "Astra Pro",
    "Orbbec Astra"
   ]
  },
  "AST_662abed1": {
   "name": "口腔手术辅助递械姿态计算方法专利",
   "type": "tool",
   "source": "https://www.xjishu.com/zhuanli/05/202510356217.html",
   "aliases": [
    "口腔手术递械姿态",
    "CN202510356217",
    "武汉欧若博"
   ]
  },
  "AST_58a4b516": {
   "name": "STAR KUKA LWR Robot",
   "type": "robot",
   "source": "https://doi.org/10.1126/scirobotics.aar6614",
   "aliases": [
    "STAR KUKA"
   ]
  },
  "AST_e905e051": {
   "name": "STAR NVD Tracking System",
   "type": "tool",
   "source": "https://doi.org/10.1126/scirobotics.aar6614",
   "aliases": [
    "NVD System"
   ]
  },
  "AST_35a8e929": {
   "name": "MEDiC Framework",
   "type": "framework",
   "source": "https://arxiv.org/abs/2409.14287",
   "aliases": [
    "MEDiC Software"
   ]
  },
  "AST_5857cede": {
   "name": "MEDiC Visual Servoing Controller",
   "type": "tool",
   "source": "https://arxiv.org/abs/2409.14287",
   "aliases": [
    "MEDiC VS Controller"
   ]
  },
  "AST_b51a1b5d": {
   "name": "MEDiC APS Optimizer",
   "type": "model",
   "source": "https://arxiv.org/abs/2409.14287",
   "aliases": [
    "MEDiC APS"
   ]
  },
  "AST_2d9f0503": {
   "name": "MEDiC Phantom Dataset",
   "type": "dataset",
   "source": "https://arxiv.org/abs/2409.14287",
   "aliases": [
    "MEDiC Phantom"
   ]
  },
  "AST_35fcd370": {
   "name": "Foehn 2017 RSS MPCC",
   "type": "tool",
   "source": "http://rpg.ifi.uzh.ch/docs/RSS17_Foehn.pdf",
   "aliases": [
    "Foehn 2017",
    "Foehn RSS MPCC",
    "cable-suspended payload MPCC"
   ]
  },
  "AST_65e1a877": {
   "name": "Bjornsen 2022 ICRA L1Quad",
   "type": "tool",
   "source": "https://arxiv.org/abs/2205.06908",
   "aliases": [
    "Bjornsen 2022",
    "L1 Adaptive Augmentation Geometric",
    "L1Quad ICRA 2022"
   ]
  },
  "AST_d468da3d": {
   "name": "Palunko 2012 ICRA",
   "type": "tool",
   "source": "https://ieeexplore.ieee.org/document/6225213",
   "aliases": [
    "Palunko 2012",
    "swing-free DP trajectory",
    "Palunko Fierro Cruz"
   ]
  },
  "AST_8eab6a8e": {
   "name": "Saeidi et al. 2022 Science Robotics",
   "type": "tool",
   "source": "https://www.science.org/doi/10.1126/scirobotics.abj2908",
   "aliases": [
    "Saeidi 2022"
   ]
  },
  "AST_c6b55bf7": {
   "name": "Shademan et al. 2016 Sci Transl Med",
   "type": "tool",
   "source": "https://doi.org/10.1126/scitranslmed.aad9398",
   "aliases": [
    "Shademan 2016"
   ]
  },
  "AST_aa8311cc": {
   "name": "Saeidi et al. 2019 ICRA",
   "type": "tool",
   "source": "IEEE ICRA 2019:1541-1547",
   "aliases": [
    "Saeidi 2019"
   ]
  },
  "AST_5fdade90": {
   "name": "Leonard et al. 2014 IEEE T-BME",
   "type": "tool",
   "source": "IEEE T-BME 61(5):1305-1317",
   "aliases": [
    "Leonard 2014"
   ]
  },
  "AST_b1925098": {
   "name": "Le et al. 2018 J Biomed Opt",
   "type": "tool",
   "source": "J Biomed Opt 23:1-10",
   "aliases": [
    "Le 2018"
   ]
  },
  "AST_0ba27568": {
   "name": "Decker et al. 2017 IEEE T-BME",
   "type": "tool",
   "source": "IEEE T-BME 64(2):549-556",
   "aliases": [
    "Decker 2017"
   ]
  },
  "AST_903fca03": {
   "name": "SurRoL",
   "type": "framework",
   "source": "https://github.com/med-air/SurRoL",
   "aliases": [
    "SurRoL",
    "Surgical RL"
   ]
  },
  "AST_c8d92190": {
   "name": "AutoMoDe",
   "type": "framework",
   "source": "https://github.com/iridia-ulb/AutoMoDe",
   "aliases": [
    "Automatic Modular Design"
   ]
  },
  "AST_e1b81220": {
   "name": "SIERRA",
   "type": "framework",
   "source": "https://github.com/jharwell/sierra",
   "aliases": [
    "reSearch pIpEline for Reproducibility Reusability and Automation"
   ]
  },
  "AST_2ce8b76e": {
   "name": "FORDYCA",
   "type": "framework",
   "source": "https://github.com/jharwell/fordyca",
   "aliases": [
    "FORaging DYnamic Cluster Allocation"
   ]
  },
  "AST_f6c893a3": {
   "name": "cosm",
   "type": "framework",
   "source": "https://github.com/jharwell/cosm",
   "aliases": [
    "COre SwarM library"
   ]
  },
  "AST_98151caa": {
   "name": "Buzz",
   "type": "framework",
   "source": "https://github.com/buzz-lang/Buzz",
   "aliases": []
  },
  "AST_d760efc4": {
   "name": "Khepera IV",
   "type": "robot",
   "source": "https://www.k-team.com/khepera-iv",
   "aliases": [
    "KheperaIV",
    "Khepera-IV"
   ]
  },
  "AST_2acc817e": {
   "name": "robotics-course",
   "type": "framework",
   "source": "https://github.com/MarcToussaint/robotics-course",
   "aliases": [
    "Toussaint Robotics Course"
   ]
  },
  "AST_14e53d97": {
   "name": "PLCopen Motion Control",
   "type": "framework",
   "source": "https://www.plcopen.org/technical-activities/motion-control",
   "aliases": [
    "PLCopen MC",
    "PLCopen Motion"
   ]
  },
  "AST_19cc9324": {
   "name": "pybotics",
   "type": "tool",
   "source": "https://github.com/engnadeau/pybotics",
   "aliases": [
    "pybotics Python robotics toolbox",
    "engnadeau pybotics"
   ]
  },
  "AST_2b4e7d0f": {
   "name": "Interlink FSR 402",
   "type": "tool",
   "source": "https://www.interlinkelectronics.com/fsr-402",
   "aliases": [
    "Interlink FSR-402",
    "Force Sensitive Resistor 402",
    "薄膜压力传感器 402"
   ]
  },
  "AST_e304a6de": {
   "name": "XHAND1",
   "type": "robot",
   "source": "[待核查]",
   "aliases": []
  },
  "AST_1d7fb688": {
   "name": "iFEM2.0 Inverse Finite Element Force Reconstruction",
   "type": "model",
   "source": "https://ieeexplore.ieee.org/document/10758225",
   "aliases": []
  },
  "AST_71e56588": {
   "name": "GelSlim 3.0 Vision-Based Tactile Sensor",
   "type": "tool",
   "source": "https://ieeexplore.ieee.org/document/10758225",
   "aliases": []
  },
  "AST_49b4497d": {
   "name": "ATI Gamma NET Force Torque Sensor",
   "type": "tool",
   "source": "https://www.ati-ia.com/products/ft/ft_Net.aspx",
   "aliases": []
  },
  "AST_2906380f": {
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    "Spatio-temporal Diffusion Point Processes"
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   "name": "neural_stpp Datasets",
   "type": "dataset",
   "source": "https://github.com/facebookresearch/neural_stpp",
   "aliases": [
    "STPP Datasets",
    "neural_stpp Data",
    "时空点过程数据集"
   ]
  },
  "AST_9d7c481f": {
   "name": "Firby 1987 Reactive Action Packages",
   "type": "paper",
   "source": "https://cdn.aaai.org/AAAI/1987/AAAI87-036.pdf",
   "aliases": [
    "RAPs",
    "Reactive Action Package"
   ]
  },
  "AST_25a8619f": {
   "name": "Gat 1992 Atlantis Architecture",
   "type": "paper",
   "source": "https://www.aaai.org/Library/AAAI/1992/ [待核查：正确论文编号未确认]",
   "aliases": [
    "Atlantis"
   ]
  },
  "AST_1c41cfe4": {
   "name": "Google Earth Engine",
   "type": "framework",
   "source": "https://earthengine.google.com/",
   "aliases": [
    "GEE",
    "earthengine",
    "Google Earth Engine API"
   ]
  },
  "AST_1aa4bff8": {
   "name": "slugs (Extensible GR(1) Synthesizer)",
   "type": "tool",
   "source": "https://github.com/VerifiableRobotics/slugs",
   "aliases": []
  },
  "AST_0e75e9ce": {
   "name": "FLLOAT (LTLf/LDLf on Finite Traces)",
   "type": "package",
   "source": "https://github.com/whitemech/flloat",
   "aliases": []
  },
  "AST_8fd412e7": {
   "name": "pythomata (Python Automata Theory)",
   "type": "package",
   "source": "https://github.com/whitemech/pythomata",
   "aliases": []
  },
  "AST_94fcd2be": {
   "name": "VITA",
   "type": "model",
   "source": "https://github.com/sukjunhwang/VITA",
   "aliases": [
    "Video Instance Segmentation via Object Token Association"
   ]
  },
  "AST_3296b3bf": {
   "name": "MinVIS",
   "type": "model",
   "source": "https://github.com/NVlabs/MinVIS",
   "aliases": [
    "Minimal Video Instance Segmentation"
   ]
  },
  "AST_eb1d8cc6": {
   "name": "IDOL",
   "type": "model",
   "source": "https://github.com/wjn922/IDOL",
   "aliases": [
    "In Defense of Online Models for VIS"
   ]
  },
  "AST_b2def6e0": {
   "name": "SeqFormer",
   "type": "model",
   "source": "https://github.com/wjf5203/SeqFormer",
   "aliases": [
    "Sequential Transformer for VIS"
   ]
  },
  "AST_ed942cad": {
   "name": "VisTR",
   "type": "model",
   "source": "https://github.com/Wujiezhou/VisTR",
   "aliases": [
    "End-to-End Video Instance Segmentation Transformer"
   ]
  },
  "AST_251ef702": {
   "name": "YouTube-VIS",
   "type": "dataset",
   "source": "https://youtube-vos.org/dataset/vis/",
   "aliases": [
    "YouTube-VIS 2019",
    "YouTube-VIS 2021"
   ]
  },
  "AST_6b454e99": {
   "name": "YouTube-VIS CodaLab Evaluation Server",
   "type": "benchmark",
   "source": "https://competitions.codalab.org/competitions/20128",
   "aliases": [
    "CodaLab VIS eval"
   ]
  },
  "AST_218e3687": {
   "name": "ReferFormer",
   "type": "model",
   "source": "https://github.com/wjn922/ReferFormer",
   "aliases": [
    "Referring VOS with Language-Guided Queries"
   ]
  },
  "AST_701a2e1a": {
   "name": "OnlineRefer",
   "type": "model",
   "source": "https://github.com/wjn922/OnlineRefer",
   "aliases": [
    "Online Referring VOS"
   ]
  },
  "AST_1cbae87e": {
   "name": "Ref-YouTube-VOS",
   "type": "dataset",
   "source": "https://youtube-vos.org/dataset/rvos/",
   "aliases": [
    "Ref-YTVOS",
    "Referring YouTube-VOS"
   ]
  },
  "AST_971c902b": {
   "name": "STUMPY",
   "type": "framework",
   "source": "https://github.com/TDAmeritrade/stumpy",
   "aliases": [
    "STUMPY Matrix Profile Library"
   ]
  },
  "AST_4cfe13cd": {
   "name": "SPMF",
   "type": "framework",
   "source": "https://www.philippe-fournier-viger.com/spmf/",
   "aliases": [
    "SPMF Data Mining Library",
    "Sequential Pattern Mining Framework"
   ]
  },
  "AST_f8017ecc": {
   "name": "TIPSem",
   "type": "tool",
   "source": "https://aclanthology.org/S10-1070/",
   "aliases": [
    "TIPSem",
    "Temporal Information Processing with SEMantic roles"
   ]
  },
  "AST_88a2f070": {
   "name": "CogCompNLP",
   "type": "framework",
   "source": "https://github.com/CogComp/cogcomp-nlp",
   "aliases": [
    "CogCompNLP",
    "CogComp NLP",
    "cogcomp-nlp"
   ]
  },
  "AST_832376e7": {
   "name": "TemProb",
   "type": "model",
   "source": "https://github.com/CogComp/TemProb-NAACL18",
   "aliases": [
    "TemProb",
    "Temporal Probability Resource"
   ]
  },
  "AST_d6bc66b5": {
   "name": "Allen 1983 Interval Algebra",
   "type": "tool",
   "source": "https://dl.acm.org/doi/10.1145/182.358434",
   "aliases": [
    "Allen 1983",
    "Allen Interval Algebra",
    "Maintaining knowledge about temporal intervals"
   ]
  },
  "AST_390ffdf9": {
   "name": "Allen Relation Composition Table",
   "type": "tool",
   "source": "https://dl.acm.org/doi/10.1145/182.358434",
   "aliases": [
    "Allen Composition Table",
    "Allen Table I",
    "IA-13 Composition Table"
   ]
  },
  "AST_7a2f3fd1": {
   "name": "Sparse4D",
   "type": "model",
   "source": "[待核查]",
   "aliases": [
    "Sparse4D v3",
    "Horizon Sparse4D"
   ]
  },
  "AST_6c178a84": {
   "name": "MPPNet",
   "type": "model",
   "source": "https://github.com/open-mmlab/OpenPCDet",
   "aliases": [
    "MPPNet Multi-Frame Detection",
    "Multi-Frame Proposal Net"
   ]
  },
  "AST_8f56f504": {
   "name": "robot_pose_ekf",
   "type": "ros_package",
   "source": "https://github.com/ros-planning/robot_pose_ekf",
   "aliases": [
    "robot_pose_ekf",
    "ROS 6D EKF"
   ]
  },
  "AST_797109f5": {
   "name": "TFD",
   "type": "tool",
   "source": "[待核查] 学术发布页（Eyerich, Helmert 等）",
   "aliases": [
    "Temporal Fast Downward"
   ]
  },
  "AST_5d959d7a": {
   "name": "RiDDLe",
   "type": "package",
   "source": "https://github.com/pstlab/RiDDLe",
   "aliases": [
    "RiDDLe",
    "riddle-lang",
    "pstlab RiDDLe"
   ]
  },
  "AST_c773c889": {
   "name": "KeeN",
   "type": "tool",
   "source": "https://github.com/ugilio/keen",
   "aliases": [
    "KeeN",
    "keen",
    "Knowledge Engineering Environment"
   ]
  },
  "AST_cc228dae": {
   "name": "continuum_robot_rviz",
   "type": "ros_package",
   "source": "https://github.com/Shaswat2001/continuum_robot_rviz",
   "aliases": []
  },
  "AST_18fba771": {
   "name": "SCAN-Planner",
   "type": "tool",
   "source": "https://github.com/leggedrobotics/SCAN-Planner",
   "aliases": []
  },
  "AST_9015e42c": {
   "name": "GTOS-mobile",
   "type": "dataset",
   "source": "https://github.com/GTOS-mobile",
   "aliases": []
  },
  "AST_c6701725": {
   "name": "Garmin LidarLite v3 Rangefinder",
   "type": "tool",
   "source": "https://docs.px4.io/main/en/sensor_distance_sensor.html",
   "aliases": [
    "LidarLite v3",
    "Garmin laser rangefinder",
    "PX4 down-looking rangefinder"
   ]
  },
  "AST_94311742": {
   "name": "Wheel-SLAM",
   "type": "tool",
   "source": "https://github.com/i2Nav-WHU/Wheel-SLAM",
   "aliases": [
    "i2Nav-WHU Wheel-SLAM",
    "wheel-IMU terrain SLAM",
    "RBPF roll terrain mapping"
   ]
  },
  "AST_d0d3b9aa": {
   "name": "tercom_nav",
   "type": "ros_package",
   "source": "https://github.com/mzahana/tercom_nav",
   "aliases": [
    "tercom_nav",
    "TERCOM+ESKF"
   ]
  },
  "AST_20fa5bce": {
   "name": "elevation",
   "type": "package",
   "source": "https://github.com/bopen/elevation",
   "aliases": [
    "elevation (PyPI)",
    "bopen/elevation"
   ]
  },
  "AST_7955c56a": {
   "name": "gps_denied_navigation_sim",
   "type": "simulator",
   "source": "https://github.com/riotu-lab/gps_denied_navigation_sim",
   "aliases": [
    "gps_denied_navigation_sim",
    "RIoTU sim"
   ]
  },
  "AST_84e889d0": {
   "name": "STEGO",
   "type": "framework",
   "source": "https://github.com/mhamilton723/STEGO",
   "aliases": [
    "Unsupervised Semantic Segmentation by Distilling Feature Correspondences",
    "Self-supervised Transformer with Energy-based Graph Optimization"
   ]
  },
  "AST_5c9595ec": {
   "name": "MVS-Texturing",
   "type": "tool",
   "source": "https://github.com/nmoehrle/mvs-texturing",
   "aliases": [
    "mvs-texturing",
    "Waechter 2014 Texturing"
   ]
  },
  "AST_3a9bb3c3": {
   "name": "Agisoft Metashape",
   "type": "package",
   "source": "https://www.agisoft.com/",
   "aliases": [
    "Agisoft PhotoScan",
    "Metashape"
   ]
  },
  "AST_87fa26e7": {
   "name": "RobustPhotometricStereo",
   "type": "package",
   "source": "https://github.com/yasumat/RobustPhotometricStereo",
   "aliases": [
    "RobustPS",
    "yasumat RobustPhotometricStereo"
   ]
  },
  "AST_25eb7bf5": {
   "name": "Deep Photometric Stereo Network",
   "type": "package",
   "source": "https://github.com/hiroaki-santo/deep-photometric-stereo-network",
   "aliases": [
    "DPSN",
    "Santo 2017 DPSN"
   ]
  },
  "AST_fcf15c83": {
   "name": "SDM-UniPS",
   "type": "package",
   "source": "https://github.com/satoshi-ikehata/SDM-UniPS-CVPR2023",
   "aliases": [
    "SDM-UniPS",
    "Ikehata 2023 UniPS",
    "Universal Photometric Stereo"
   ]
  },
  "AST_043f4367": {
   "name": "Deschaintre 2018 SVBRDF Code",
   "type": "dataset",
   "source": "https://users.cs.cornell.edu/projects/svbrdf/",
   "aliases": [
    "Deschaintre 2018",
    "Single-Image SVBRDF Capture",
    "Rendering-Aware Deep Network"
   ]
  },
  "AST_1993fb99": {
   "name": "Adobe Substance 3D Sampler",
   "type": "framework",
   "source": "https://www.adobe.com/products/substance3d-sampler.html",
   "aliases": [
    "Substance Sampler",
    "Substance Alchemist",
    "Adobe Sampler"
   ]
  },
  "AST_84fe450f": {
   "name": "Li 2018 Pre-Net",
   "type": "model",
   "source": "[待核查]",
   "aliases": [
    "Pre-Net",
    "DISAPre-Net",
    "Li 2018 SVBRDF"
   ]
  },
  "AST_22aac542": {
   "name": "Materialize",
   "type": "tool",
   "source": "https://boundingboxsoftware.com/materialize/",
   "aliases": [
    "Materialize PBR",
    "Bounding Box Materialize"
   ]
  },
  "AST_420c49b9": {
   "name": "MVE",
   "type": "tool",
   "source": "https://github.com/simonfuhrmann/mve",
   "aliases": [
    "Multi-View Environment",
    "MVE"
   ]
  },
  "AST_9e5d7566": {
   "name": "mapMAP",
   "type": "tool",
   "source": "https://github.com/dthuerck/mapmap_cpu",
   "aliases": [
    "mapmap",
    "mapmap_cpu",
    "mapMAP MRF Solver"
   ]
  },
  "AST_d8899f7d": {
   "name": "rayint",
   "type": "tool",
   "source": "https://github.com/nmoehrle/rayint",
   "aliases": [
    "rayint",
    "Ray Intersection"
   ]
  },
  "AST_6bc12862": {
   "name": "ElasticReconstruction",
   "type": "tool",
   "source": "https://github.com/qianyizh/ElasticReconstruction",
   "aliases": [
    "ElasticReconstruction Stanford",
    "Zhou ElasticReconstruction"
   ]
  },
  "AST_0919a4a3": {
   "name": "xatlas",
   "type": "tool",
   "source": "https://github.com/jpcy/xatlas",
   "aliases": [
    "xatlas",
    "jpcy xatlas"
   ]
  },
  "AST_4382ae88": {
   "name": "UVAtlas",
   "type": "tool",
   "source": "https://github.com/microsoft/UVAtlas",
   "aliases": [
    "Microsoft UVAtlas",
    "UVAtlas"
   ]
  },
  "AST_9694fca9": {
   "name": "CGAL Surface_mesh_parameterization",
   "type": "package",
   "source": "https://doc.cgal.org/latest/Surface_mesh_parameterization/",
   "aliases": [
    "CGAL SMP",
    "CGAL Surface Mesh Parameterization",
    "CGAL parameterization"
   ]
  },
  "AST_a87c0bbf": {
   "name": "Ptex",
   "type": "tool",
   "source": "https://github.com/wdas/ptex",
   "aliases": [
    "Ptex",
    "Disney Ptex",
    "Per-face Texture"
   ]
  },
  "AST_3985748f": {
   "name": "Penn Haptic Texture Dataset",
   "type": "dataset",
   "source": "[待核查] https://haptics.seas.upenn.edu/ 或 Culbertson 个人主页",
   "aliases": [
    "Penn Texture Dataset",
    "Culbertson Texture Dataset"
   ]
  },
  "AST_3e448bf2": {
   "name": "TeslaTouch",
   "type": "tool",
   "source": "[待核查] http://www.disneyresearch.com/project/teslatouch/",
   "aliases": [
    "Disney electrovibration prototype",
    "Bau TeslaTouch"
   ]
  },
  "AST_d1196234": {
   "name": "T-Pad",
   "type": "tool",
   "source": "[待核查] https://www.tactilelabs.com/ 或 Northwestern T-Pad 项目页",
   "aliases": [
    "TactileLabs T-Pad",
    "Northwestern T-Pad",
    "T-Pad Phone"
   ]
  },
  "AST_0fde268d": {
   "name": "VibraForge",
   "type": "tool",
   "source": "https://arxiv.org/abs/2409.17420",
   "aliases": [
    "VibraForge toolkit"
   ]
  },
  "AST_3279c940": {
   "name": "Coq",
   "type": "framework",
   "source": "https://github.com/coq/coq",
   "aliases": [
    "Rocq",
    "The Rocq Prover",
    "Coq Proof Assistant"
   ]
  },
  "AST_2e38d371": {
   "name": "Isabelle/HOL",
   "type": "framework",
   "source": "https://isabelle.in.tum.de/",
   "aliases": [
    "Isabelle",
    "Isabelle/HOL",
    "Isabelle Proof Assistant"
   ]
  },
  "AST_ef6e1bb0": {
   "name": "ACL2 Theorem Prover",
   "type": "framework",
   "source": "https://github.com/acl2/acl2",
   "aliases": [
    "ACL2",
    "A Computational Logic for Applicative Common Lisp"
   ]
  },
  "AST_1bd4f7ed": {
   "name": "HOL4 Theorem Prover",
   "type": "framework",
   "source": "https://github.com/HOL-Theorem-Prover/HOL",
   "aliases": [
    "HOL4",
    "HOL Theorem Prover",
    "Higher Order Logic theorem prover"
   ]
  },
  "AST_98264c0a": {
   "name": "flirpy",
   "type": "tool",
   "source": "https://github.com/LJMUAstroecology/flirpy",
   "aliases": []
  },
  "AST_e2bdc18d": {
   "name": "flir_image_extractor",
   "type": "tool",
   "source": "https://github.com/nationaldronesau/FlirImageExtractor",
   "aliases": []
  },
  "AST_2d104095": {
   "name": "InfraredSolarModules",
   "type": "dataset",
   "source": "https://github.com/RaptorMaps/InfraredSolarModules",
   "aliases": []
  },
  "AST_d29b1e39": {
   "name": "HOTSPOT-YOLO",
   "type": "model",
   "source": "https://arxiv.org/abs/2508.18912",
   "aliases": []
  },
  "AST_fbc25db6": {
   "name": "AnomalyGPT",
   "type": "tool",
   "source": "https://github.com/CASIA-IVA-Lab/AnomalyGPT",
   "aliases": []
  },
  "AST_5252cc9e": {
   "name": "Vicuna-7B",
   "type": "model",
   "source": "https://github.com/lm-sys/FastChat",
   "aliases": []
  },
  "AST_6c914976": {
   "name": "YOLO/Ultralytics",
   "type": "tool",
   "source": "https://github.com/ultralytics/ultralytics",
   "aliases": []
  },
  "AST_288d95a7": {
   "name": "RIDERS",
   "type": "tool",
   "source": "https://github.com/MMOCKING/RIDERS",
   "aliases": [
    "RIDERS",
    "Radar-Infrared Depth Estimation"
   ]
  },
  "AST_4d66676e": {
   "name": "ZJU-Multispectrum",
   "type": "dataset",
   "source": "https://github.com/MMOCKING/RIDERS",
   "aliases": [
    "ZJU-Multispectrum",
    "ZJU Multispectrum Dataset"
   ]
  },
  "AST_0c6fa308": {
   "name": "MS2 Multi-Spectral Stereo Dataset",
   "type": "dataset",
   "source": "[待核查，CVPR 2023 Kim 团队]",
   "aliases": [
    "MS²",
    "Multi-Spectral Stereo Dataset"
   ]
  },
  "AST_931341dc": {
   "name": "R-LiViT",
   "type": "dataset",
   "source": "[XITASO + LiangDao, 2025]",
   "aliases": [
    "R-LiViT",
    "LiDAR-Visual-Thermal Dataset"
   ]
  },
  "AST_3e2a96bd": {
   "name": "FLIR ADAS Thermal Dataset",
   "type": "dataset",
   "source": "https://www.flir.com/oem/adas/adas-dataset-dl/",
   "aliases": [
    "FLIR ADAS",
    "FLIR Thermal Dataset"
   ]
  },
  "AST_8e37c0d4": {
   "name": "FLIR Boson Thermal Camera",
   "type": "tool",
   "source": "https://www.flir.com/products/boson/",
   "aliases": [
    "FLIR Boson",
    "Boson"
   ]
  },
  "AST_29381848": {
   "name": "LLVIP",
   "type": "dataset",
   "source": "https://github.com/bupt-ai-cz/LLVIP",
   "aliases": [
    "LLVIP",
    "Low-light Visible-infrared Paired Dataset"
   ]
  },
  "AST_a63de99b": {
   "name": "HIT-UAV Infrared Thermal Dataset",
   "type": "dataset",
   "source": "https://github.com/BigBigLiang-mars/HIT-UAV-Infrared-Thermal-Dataset",
   "aliases": [
    "HIT-UAV",
    "High-altitude Infrared Thermal UAV Dataset"
   ]
  },
  "AST_41e60498": {
   "name": "DJI Mavic 3 Thermal",
   "type": "robot",
   "source": "https://www.dji.com/mavic-3/thermal",
   "aliases": [
    "DJI Mavic 3 Thermal",
    "Mavic 3 Thermal",
    "M3T"
   ]
  },
  "AST_14b23a09": {
   "name": "FLIR Vue Pro Thermal Camera",
   "type": "tool",
   "source": "https://www.flir.com/products/vue-pro/",
   "aliases": [
    "FLIR Vue Pro",
    "Vue Pro"
   ]
  },
  "AST_e98d9c38": {
   "name": "pyadjoint",
   "type": "tool",
   "source": "https://github.com/dolfin-adjoint/pyadjoint",
   "aliases": []
  },
  "AST_dab152ba": {
   "name": "Top88",
   "type": "tool",
   "source": "https://doi.org/10.1007/s00158-010-0594-7",
   "aliases": []
  },
  "AST_5af91840": {
   "name": "SMT (Surrogate Modeling Toolbox)",
   "type": "tool",
   "source": "https://github.com/SMTorg/smt",
   "aliases": []
  },
  "AST_e8b9d893": {
   "name": "EN ISO 13732-1",
   "type": "tool",
   "source": "https://www.iso.org/standard/56640.html",
   "aliases": [
    "ISO 13732-1",
    "EN ISO 13732-1:2008"
   ]
  },
  "AST_ed41e562": {
   "name": "FLIR Spinnaker SDK",
   "type": "package",
   "source": "https://github.com/Teledyne-MV/Spinnaker-SDK",
   "aliases": [
    "Spinnaker SDK",
    "PySpin",
    "FLIR Spinnaker",
    "Teledyne Spinnaker"
   ]
  },
  "AST_515a2cbb": {
   "name": "nvidia-smi",
   "type": "tool",
   "source": "https://developer.nvidia.com/nvidia-system-management-interface",
   "aliases": [
    "NVIDIA SMI",
    "nvidia-smi CLI"
   ]
  },
  "AST_84e8bd84": {
   "name": "DenseFuse",
   "type": "model",
   "source": "https://github.com/hli1221/imagefusion_densefuse",
   "aliases": [
    "imagefusion_densefuse"
   ]
  },
  "AST_c9671508": {
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   "type": "model",
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  },
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   "type": "model",
   "source": "https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct",
   "aliases": [
    "Qwen2.5-VL-3B-Instruct",
    "Qwen-VL-3B"
   ]
  },
  "AST_8284054d": {
   "name": "π0.5-LIBERO",
   "type": "model",
   "source": "gs://openpi-assets/checkpoints/pi05_libero",
   "aliases": [
    "pi05_libero",
    "π0.5 LIBERO"
   ]
  },
  "AST_e1eb6370": {
   "name": "π0.5-DROID",
   "type": "model",
   "source": "gs://openpi-assets/checkpoints/pi05_droid",
   "aliases": [
    "pi05_droid",
    "π0.5 DROID"
   ]
  },
  "AST_f8ae2631": {
   "name": "RoboDojo XPolicyLab",
   "type": "framework",
   "source": "https://robodojo-benchmark.github.io/",
   "aliases": [
    "XPolicyLab",
    "RoboDojo code"
   ]
  },
  "AST_e2e0548d": {
   "name": "TinyVLA",
   "type": "tool",
   "source": "https://github.com/liyaxuanliyaxuan/TinyVLA",
   "aliases": [
    "liyaxuanliyaxuan/TinyVLA",
    "Tiny Vision-Language-Action"
   ]
  },
  "AST_148ccbe7": {
   "name": "VITRA",
   "type": "framework",
   "source": "https://github.com/microsoft/VITRA",
   "aliases": [
    "VITRA-1M",
    "VITRA-VLA-3B",
    "Vision-language pretraining from in-the-Wild egocentric videos"
   ]
  },
  "AST_f2aeee08": {
   "name": "CLAP (Contrastive Latent Action Pretraining)",
   "type": "framework",
   "source": "https://github.com/LinShan-Bin/OpenCLAP",
   "aliases": [
    "Contrastive Latent Action Pretraining",
    "OpenCLAP",
    "CLAP-NTP",
    "CLAP-RF"
   ]
  },
  "AST_e3009103": {
   "name": "EgoScale",
   "type": "framework",
   "source": "https://research.nvidia.com/labs/gear/egoscale/",
   "aliases": [
    "EgoScale Framework",
    "20k Hours Egocentric Pretraining"
   ]
  },
  "AST_dd87e577": {
   "name": "EgoExoLearn",
   "type": "dataset",
   "source": "https://github.com/OpenGVLab/EgoExoLearn",
   "aliases": [
    "Ego-Exo Learn Dataset"
   ]
  },
  "AST_e53b2752": {
   "name": "ByteBOT",
   "type": "tool",
   "source": "https://cloud.tencent.cn/developer/news/955457",
   "aliases": [
    "ByteDance ObjectNav"
   ]
  },
  "AST_e816b571": {
   "name": "VQAv2",
   "type": "dataset",
   "source": "https://visualqa.org/",
   "aliases": [
    "VQA v2",
    "Visual Question Answering v2"
   ]
  },
  "AST_18fc6df5": {
   "name": "ricky0123/vad-web",
   "type": "package",
   "source": "https://github.com/ricky0123/vad",
   "aliases": [
    "@ricky0123/vad-web",
    "vad-web",
    "ricky0123 vad",
    "browser VAD"
   ]
  },
  "AST_198c0fac": {
   "name": "AVA-Speech",
   "type": "dataset",
   "source": "https://github.com/abavesh/AVA-Speech",
   "aliases": [
    "AVA-Speech",
    "AVA Speech dataset"
   ]
  },
  "AST_7fb4d505": {
   "name": "S3PRL",
   "type": "framework",
   "source": "https://github.com/s3prl/s3prl",
   "aliases": [
    "Self-Supervised Speech Pre-training and Representation Learning"
   ]
  },
  "AST_d6882e04": {
   "name": "SUPERB",
   "type": "benchmark",
   "source": "https://github.com/s3prl/s3prl",
   "aliases": [
    "Speech processing Universal PERformance Benchmark"
   ]
  },
  "AST_7f714e00": {
   "name": "CNN14",
   "type": "model",
   "source": "https://github.com/qiuqiangkong/audioset_tagging_cnn",
   "aliases": [
    "PANNs CNN14"
   ]
  },
  "AST_42d3c618": {
   "name": "BVC (Learning Blind Video Temporal Consistency)",
   "type": "model",
   "source": "https://github.com/phoenix104104/fast_blind_video_consistency",
   "aliases": [
    "fast_blind_video_consistency",
    "Learning Blind Video Temporal Consistency",
    "BVC"
   ]
  },
  "AST_191adaa3": {
   "name": "DVP (Deep Video Prior)",
   "type": "model",
   "source": "https://github.com/ChenyangLEI/deep-video-prior",
   "aliases": [
    "deep-video-prior",
    "DVP",
    "Deep Video Prior"
   ]
  },
  "AST_8ad1782e": {
   "name": "All-In-One Deflicker",
   "type": "model",
   "source": "https://github.com/ChenyangLEI/All-In-One-Deflicker",
   "aliases": [
    "All-In-One-Deflicker",
    "Blind Video Deflickering",
    "Neural Filtering Atlas"
   ]
  },
  "AST_5313ce0d": {
   "name": "VPN (Video Propagation Networks)",
   "type": "framework",
   "source": "https://github.com/varunjampani/video_propagation_networks",
   "aliases": [
    "VPN",
    "Video Propagation Networks",
    "temporal bilateral network"
   ]
  },
  "AST_d96904b5": {
   "name": "MaskRNN (Instance-Level Video Object Segmentation)",
   "type": "model",
   "source": "https://arxiv.org/abs/1803.11987",
   "aliases": [
    "MaskRNN",
    "Instance-Level VOS",
    "recurrent mask proposal"
   ]
  },
  "AST_cc0e4748": {
   "name": "AuxAdapt",
   "type": "model",
   "source": "https://arxiv.org/abs/2110.12369",
   "aliases": [
    "AuxAdapt",
    "AuxNet TTA",
    "Stable Test-Time Adaptation VSS"
   ]
  },
  "AST_e18130fd": {
   "name": "VDBFusion",
   "type": "package",
   "source": "https://github.com/PRBonn/vdbfusion",
   "aliases": [
    "vdbfusion",
    "VDBFusion"
   ]
  },
  "AST_fa72db71": {
   "name": "vdbfusion_ros",
   "type": "ros_package",
   "source": "https://github.com/PRBonn/vdbfusion_ros",
   "aliases": [
    "vdbfusion_ros",
    "ROS-VDBFusion"
   ]
  },
  "AST_e686277e": {
   "name": "VDB-Mapping",
   "type": "package",
   "source": "https://github.com/fzi-forschungszentrum-informatik/vdb_mapping",
   "aliases": [
    "VDB-Mapping",
    "vdb_mapping"
   ]
  },
  "AST_7fbdc219": {
   "name": "VoxelMap++",
   "type": "tool",
   "source": "https://github.com/uestic-icsp/VoxelMapPlus_Public",
   "aliases": [
    "VoxelMap Plus Plus",
    "uestc-icsp/VoxelMapPlus"
   ]
  },
  "AST_47702dcc": {
   "name": "C3P-VoxelMap",
   "type": "tool",
   "source": "https://github.com/deptrum/c3p-voxelmap",
   "aliases": [
    "C3P-VoxelMap IROS 2024",
    "Yixi-Cai/C3P-VoxelMap",
    "deptrum/c3p-voxelmap"
   ]
  },
  "AST_e0dec3d7": {
   "name": "VO Foundation Paper",
   "type": "paper",
   "source": "https://journals.sagepub.com/doi/10.1177/027836499801700706",
   "aliases": [
    "Fiorini Shiller 1998",
    "IJRR 1998 VO paper"
   ]
  },
  "AST_2432f8d7": {
   "name": "RVO Paper",
   "type": "paper",
   "source": "https://gamma.cs.unc.edu/RVO/",
   "aliases": [
    "van den Berg 2008 ICRA",
    "Reciprocal Velocity Obstacles"
   ]
  },
  "AST_3fdb0e4e": {
   "name": "vuer",
   "type": "package",
   "source": "https://github.com/vuer-ai/vuer",
   "aliases": [
    "Vuer"
   ]
  },
  "AST_ba195dcc": {
   "name": "DART (Dexterous Augmented Reality Teleoperation)",
   "type": "paper",
   "source": "https://arxiv.org/abs/2411.02214",
   "aliases": [
    "DexHub",
    "DART teleoperation"
   ]
  },
  "AST_0f153867": {
   "name": "XRoboToolkit",
   "type": "package",
   "source": "https://github.com/Pico-Developer/XRoboToolkit",
   "aliases": [
    "PICO XRoboToolkit",
    "XR-Robotics teleop"
   ]
  },
  "AST_d005d8d3": {
   "name": "PlaCo",
   "type": "framework",
   "source": "https://github.com/rhoban/placo",
   "aliases": [
    "placo",
    "rhoban placo"
   ]
  },
  "AST_fe5dd754": {
   "name": "CodeQL",
   "type": "tool",
   "source": "https://github.com/github/codeql",
   "aliases": []
  },
  "AST_627d5954": {
   "name": "Clair",
   "type": "tool",
   "source": "https://github.com/quay/clair",
   "aliases": []
  },
  "AST_afac5b35": {
   "name": "KNF NMP830",
   "type": "tool",
   "source": "https://knf.com/zh/cn/解决方案/泵产品/系列/隔膜气体泵-nmp-830",
   "aliases": [
    "NMP830",
    "隔膜气体泵NMP 830"
   ]
  },
  "AST_67a858fe": {
   "name": "MPX5700",
   "type": "tool",
   "source": "https://www.icsensors.com.cn/fd_sensor/freescale_mpx5700a.shtml（[待核查] 官方NXP页面另查）",
   "aliases": [
    "MPX5700系列",
    "MPX5700A"
   ]
  },
  "AST_de3ef5f7": {
   "name": "ANSYS Maxwell",
   "type": "tool",
   "source": "[待核查] ANSYS官方产品页",
   "aliases": [
    "Maxwell",
    "Ansys EM21.1"
   ]
  },
  "AST_0ed24aca": {
   "name": "NdFeB N35-N52",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "钕铁硼永磁体",
    "NdFeB Permanent Magnet"
   ]
  },
  "AST_41221fec": {
   "name": "Electromagnetic Coil Assembly",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "电磁铁线圈",
    "Electromagnet Coil"
   ]
  },
  "AST_84ddfb34": {
   "name": "爬壁机器人磁吸附组件优化设计与试验研究 (Song 2018)",
   "type": "paper",
   "source": "https://qikan.cqvip.com/Qikan/Article/Detail?id=7000859537",
   "aliases": [
    "宋伟2018",
    "磁质比优化论文"
   ]
  },
  "AST_61d19ad4": {
   "name": "Magnetic Wall-Climbing Wheels with Controllable Adhesion Reduction (Tian 2024)",
   "type": "paper",
   "source": "https://bioinbot.hkust-gz.edu.cn/publication/tian-2024/",
   "aliases": [
    "Tian 2024",
    "SMM磁轮论文"
   ]
  },
  "AST_9d1ecec7": {
   "name": "Multi-Parameter Performance Optimization of Magnetic Adhesion Unit (Zhu 2025)",
   "type": "paper",
   "source": "https://www.aminer.cn/pub/6838d812163c01c8503ff4b0/",
   "aliases": [
    "Zhu 2025",
    "可调磁吸附单元优化论文"
   ]
  },
  "AST_662b31c4": {
   "name": "Smooth Vertical Surface Climbing with Directional Adhesion (Stickybot)",
   "type": "paper",
   "source": "https://doi.org/10.1109/TRO.2007.909773",
   "aliases": [
    "Stickybot",
    "Kim 2008"
   ]
  },
  "AST_d52465ee": {
   "name": "Waalbot II: Adhesion Recovery and Improved Performance using Fibrillar Adhesives",
   "type": "paper",
   "source": "https://doi.org/10.1177/0278364910382862",
   "aliases": [
    "Waalbot II",
    "Murphy 2011"
   ]
  },
  "AST_3a98284b": {
   "name": "Soft Wall-Climbing Robots (Gu 2018)",
   "type": "paper",
   "source": "https://doi.org/10.1126/scirobotics.aat2874",
   "aliases": [
    "Soft Wall-Climbing Robot",
    "Gu 2018"
   ]
  },
  "AST_ea2dcabb": {
   "name": "Inverted and Vertical Climbing of a Quadrupedal Microrobot using Electroadhesion (HAMR-E)",
   "type": "paper",
   "source": "https://doi.org/10.1126/scirobotics.aau3038",
   "aliases": [
    "HAMR-E",
    "de Rivaz 2018"
   ]
  },
  "AST_5cf63151": {
   "name": "仿壁虎机器人脚掌的黏附性能研究及模拟微重力下黏脱附轨迹设计 (Wang 2017)",
   "type": "paper",
   "source": "https://doi.org/10.1360/N972017-00062",
   "aliases": [
    "汪中原2017",
    "仿壁虎脚掌论文"
   ]
  },
  "AST_f4321563": {
   "name": "High Voltage Electroadhesion Power Module (250-5000V)",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "高压电源模块",
    "Electroadhesion Power Supply"
   ]
  },
  "AST_c22485e2": {
   "name": "Dry Adhesive Elastomer Material (PU/PDMS/PVS)",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "干粘附弹性体",
    "PU/PDMS/PVS弹性体"
   ]
  },
  "AST_f92a033b": {
   "name": "Micro Mold Injection Molding Equipment",
   "type": "tool",
   "source": "[待核查]",
   "aliases": [
    "微模具注塑",
    "Micro-Injection Molding"
   ]
  },
  "AST_0e44736b": {
   "name": "ssscassio ros-wall-follower",
   "type": "package",
   "source": "https://github.com/ssscassio/ros-wall-follower-2-wheeled-robot",
   "aliases": []
  },
  "AST_9a294b4e": {
   "name": "MORSE Simulator",
   "type": "simulator",
   "source": "https://www.openrobots.org/morse",
   "aliases": []
  },
  "AST_e0d7414b": {
   "name": "DRL-Robot-Navigation-ROS2",
   "type": "ros_package",
   "source": "https://github.com/reiniscimurs/DRL-Robot-Navigation-ROS2",
   "aliases": []
  },
  "AST_0363d9e7": {
   "name": "Fatrop",
   "type": "tool",
   "source": "https://github.com/ethz-adrl/fatrop",
   "aliases": [
    "FATROP",
    "block-sparse interior-point"
   ]
  },
  "AST_659427dd": {
   "name": "UMI-on-Legs",
   "type": "framework",
   "source": "https://github.com/real-stanford/umi-on-legs",
   "aliases": [
    "umi-on-legs"
   ]
  },
  "AST_c7495ba9": {
   "name": "Psi-Zero",
   "type": "model",
   "source": "https://github.com/psi-lab/Psi0",
   "aliases": [
    "Psi0",
    "psi-lab/Psi0"
   ]
  },
  "AST_3b233519": {
   "name": "LLVMTA",
   "type": "tool",
   "source": "https://gitlab.cs.uni-saarland.de/reineke/llvmta",
   "aliases": [
    "LLVM-TA",
    "LLVM Timing Analyzer"
   ]
  },
  "AST_d1f21ec1": {
   "name": "Heptane",
   "type": "tool",
   "source": "https://github.com/au-ts/heptane",
   "aliases": [
    "HEPTANE"
   ]
  },
  "AST_083a584d": {
   "name": "PLATIN",
   "type": "tool",
   "source": "https://github.com/t-crest/patmos-platin",
   "aliases": [
    "PLATIN toolset",
    "patmos-platin"
   ]
  },
  "AST_2a0c8776": {
   "name": "chronovise",
   "type": "tool",
   "source": "https://github.com/federeghe/chronovise",
   "aliases": [
    "chronovise MBPTA framework"
   ]
  },
  "AST_c0a00f2c": {
   "name": "SYSU-TA",
   "type": "tool",
   "source": "https://github.com/RTS-SYSU/Timing-Analysis-Multicores",
   "aliases": [
    "Timing-Analysis-Multicores",
    "SYSU Timing Analyzer"
   ]
  },
  "AST_0a1d0e82": {
   "name": "TACLeBench",
   "type": "benchmark",
   "source": "https://github.com/tacle/tacle-bench",
   "aliases": [
    "TACLe-bench",
    "tacle-bench"
   ]
  },
  "AST_d9152e64": {
   "name": "lp_solve",
   "type": "tool",
   "source": "https://sourceforge.net/projects/lpsolve/",
   "aliases": [
    "lp_solve",
    "lpsolve"
   ]
  },
  "AST_3d93b013": {
   "name": "AffinityNet (PSA)",
   "type": "tool",
   "source": "https://github.com/jiwoon-ahn/psa",
   "aliases": [
    "PSA",
    "Pixel-level Semantic Affinity",
    "AffinityNet"
   ]
  },
  "AST_1bd7656a": {
   "name": "MCTformer",
   "type": "tool",
   "source": "https://github.com/xulianuwa/MCTformer",
   "aliases": [
    "Multi-class Token Transformer",
    "MCTformer-V1",
    "MCTformer-V2"
   ]
  },
  "AST_07522994": {
   "name": "deeplab-pytorch",
   "type": "tool",
   "source": "https://github.com/kazuto1011/deeplab-pytorch",
   "aliases": [
    "DeepLab-v2 PyTorch",
    "deeplab-pytorch (kazuto1011)"
   ]
  },
  "AST_b2f1b093": {
   "name": "PASCAL VOC 2012",
   "type": "dataset",
   "source": "http://host.robots.ox.ac.uk/pascal/VOC/voc2012/",
   "aliases": [
    "VOC2012",
    "PASCAL VOC Segmentation",
    "VOC 2012 Segmentation"
   ]
  },
  "AST_68b92f2c": {
   "name": "BoxInstSeg",
   "type": "framework",
   "source": "https://github.com/LiWentomng/BoxInstSeg",
   "aliases": [
    "BoxInstSeg Toolbox",
    "Box-Supervised Instance Segmentation Toolbox"
   ]
  },
  "AST_7bdd8c56": {
   "name": "SAM_WSSS (From SAM to CAMs)",
   "type": "tool",
   "source": "https://github.com/cskyl/SAM_WSSS",
   "aliases": [
    "From SAM to CAMs",
    "SAM Enhanced Pseudo Labels",
    "SAM_WSSS"
   ]
  },
  "AST_e0e49d7c": {
   "name": "CLIP-ES",
   "type": "tool",
   "source": "https://github.com/linyq2117/CLIP-ES",
   "aliases": [
    "CLIP is Also an Efficient Segmenter",
    "CLIP-ES WSSS",
    "Text-Driven WSSS"
   ]
  },
  "AST_95a9958b": {
   "name": "DROR/DSOR Filter",
   "type": "tool",
   "source": "https://github.com/tsender/DROR",
   "aliases": [
    "DROR",
    "DSOR",
    "Dynamic Radius Outlier Removal"
   ]
  },
  "AST_fa467295": {
   "name": "All-Weather Dataset",
   "type": "dataset",
   "source": "https://drive.google.com/file/d/1tfeBnjZX1wIhIFPl6HOzzOKOyo0GdGHl/view",
   "aliases": [
    "All-Weather",
    "Outdoor-Rain + Snow100K + Raindrop"
   ]
  },
  "AST_297e44f0": {
   "name": "TransWeather",
   "type": "model",
   "source": "https://github.com/jeya-maria-jose/TransWeather",
   "aliases": [
    "TransWeather",
    "Transformer-based Weather Removal"
   ]
  },
  "AST_0137e3ec": {
   "name": "All-in-One Bad Weather Removal",
   "type": "model",
   "source": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Li_All_in_One_Bad_Weather_Removal_Using_Architectural_Search_CVPR_2020_paper.pdf",
   "aliases": [
    "All-in-One",
    "NAS Bad Weather Removal"
   ]
  },
  "AST_9edd675e": {
   "name": "whereami",
   "type": "tool",
   "source": "https://github.com/kootenpv/whereami",
   "aliases": [
    "whereami WiFi positioning"
   ]
  },
  "AST_878d0e08": {
   "name": "SODIndoorLoc",
   "type": "dataset",
   "source": "https://github.com/renwudao24/SODIndoorLoc",
   "aliases": [
    "SOD IndoorLoc"
   ]
  },
  "AST_3999453f": {
   "name": "WIFI-SCI-Indoor-Positioning",
   "type": "model",
   "source": "https://github.com/zhangleino1/WIFI-SCI-Indoor-Positioning",
   "aliases": [
    "zhangleino1 CSI positioning"
   ]
  },
  "AST_afb7fdad": {
   "name": "Atheros CSI Tool",
   "type": "tool",
   "source": "https://github.com/xieyaxiongfly/Atheros-CSI-Tool",
   "aliases": [
    "Atheros CSI",
    "ath9k CSI Tool"
   ]
  },
  "AST_0701ba05": {
   "name": "pywifi",
   "type": "package",
   "source": "https://github.com/awkman/pywifi",
   "aliases": [
    "Python WiFi Library"
   ]
  },
  "AST_e9485132": {
   "name": "ESP-CSI",
   "type": "tool",
   "source": "https://github.com/espressif/esp-csi",
   "aliases": [
    "espressif esp-csi",
    "ESP32 CSI"
   ]
  },
  "AST_6e7ceba1": {
   "name": "Android WifiRttManager",
   "type": "tool",
   "source": "https://developer.android.com/reference/android/net/wifi/rtt/WifiRttManager",
   "aliases": [
    "WiFi RTT API",
    "Android 9 RTT"
   ]
  },
  "AST_6513b95d": {
   "name": "Tekton Pipelines",
   "type": "framework",
   "source": "https://github.com/tektoncd/pipeline",
   "aliases": [
    "Tekton",
    "Tekton Pipelines",
    "tektoncd"
   ]
  },
  "AST_86a56204": {
   "name": "Cromwell",
   "type": "framework",
   "source": "https://github.com/broadinstitute/cromwell",
   "aliases": [
    "Cromwell WDL Engine",
    "Broad Cromwell"
   ]
  },
  "AST_3547ccbd": {
   "name": "cwltool",
   "type": "tool",
   "source": "https://github.com/common-workflow-language/cwltool",
   "aliases": [
    "CWL Reference Runner",
    "cwltool CLI"
   ]
  },
  "AST_187458c3": {
   "name": "Nextflow",
   "type": "framework",
   "source": "https://github.com/nextflow-io/nextflow",
   "aliases": [
    "Nextflow Engine",
    "nf-core Engine"
   ]
  },
  "AST_c0c4df0e": {
   "name": "Toil",
   "type": "framework",
   "source": "https://github.com/DataBiosphere/toil",
   "aliases": [
    "Toil Pipeline Manager",
    "UCSC Toil"
   ]
  },
  "AST_a268821c": {
   "name": "letta-client",
   "type": "package",
   "source": "https://github.com/letta-ai/letta-python",
   "aliases": []
  },
  "AST_b01b0744": {
   "name": "langchain-core",
   "type": "package",
   "source": "https://github.com/langchain-ai/langchain",
   "aliases": []
  },
  "AST_cd7e0c47": {
   "name": "microsoft/llmlingua-2-xlm-roberta-large-meetingbank",
   "type": "model",
   "source": "https://huggingface.co/microsoft/llmlingua-2-xlm-roberta-large-meetingbank",
   "aliases": []
  },
  "AST_6bc4ef7d": {
   "name": "microsoft/llmlingua-2-bert-base-multilingual-cased-meetingbank",
   "type": "model",
   "source": "https://huggingface.co/microsoft/llmlingua-2-bert-base-multilingual-cased-meetingbank",
   "aliases": []
  },
  "AST_024baa03": {
   "name": "StreamPETR",
   "type": "tool",
   "source": "https://github.com/exiawsh/StreamPETR",
   "aliases": []
  },
  "AST_d7a4a979": {
   "name": "XPlane",
   "type": "simulator",
   "source": "https://www.x-plane.com/",
   "aliases": [
    "X-Plane"
   ]
  },
  "AST_b90f13db": {
   "name": "Ficuciello Variable Impedance Dual-Arm (TRO 2015)",
   "type": "paper",
   "source": "https://ieeexplore.ieee.org/document/7108034",
   "aliases": [
    "Ficuciello TRO 2015",
    "Variable Impedance Dual-Arm"
   ]
  },
  "AST_52bcbab2": {
   "name": "Ficuciello Sharing Impedance (IROS 2015)",
   "type": "paper",
   "source": "https://ieeexplore.ieee.org/document/7353963",
   "aliases": [
    "Ficuciello IROS 2015",
    "Sharing Impedance Control"
   ]
  },
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   "name": "RoboDreamer",
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   "source": "https://arxiv.org/abs/2404.12377",
   "aliases": [
    "RoboDreamer Compositional World Model",
    "robovideo.github.io",
    "ylqi/robodreamer"
   ]
  },
  "AST_a16b5bb4": {
   "name": "ZSD-Release",
   "type": "package",
   "source": "https://github.com/salman-h-khan/ZSD_Release",
   "aliases": [
    "ZSD_Release",
    "salman-h-khan/ZSD_Release"
   ]
  },
  "AST_ca1440ca": {
   "name": "PL-ZSD",
   "type": "package",
   "source": "https://github.com/salman-h-khan/PL-ZSD_Release",
   "aliases": [
    "PL-ZSD-Release",
    "salman-h-khan/PL-ZSD_Release"
   ]
  },
  "AST_f6b5bc9e": {
   "name": "ZSD (Rahman 2018)",
   "type": "paper",
   "source": "https://arxiv.org/abs/1803.06049",
   "aliases": [
    "Zero-Shot Detection (Rahman 2018)",
    "arXiv:1803.06049"
   ]
  },
  "AST_faf84b30": {
   "name": "Polarity Loss (Rahman 2020)",
   "type": "paper",
   "source": "https://arxiv.org/abs/1811.08982",
   "aliases": [
    "Polarity Loss",
    "Improved Visual-Semantic Alignment",
    "arXiv:1811.08982"
   ]
  },
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   "source": "https://openaccess.thecvf.com/content_ICCV_2019/papers/Rahman_Transductive_Learning_for_Zero-Shot_Object_Detection_ICCV_2019_paper.pdf",
   "aliases": [
    "Transductive ZSD",
    "Rahman ICCV 2019"
   ]
  },
  "AST_e2f17724": {
   "name": "BA-ZSD (Bansal 2019)",
   "type": "paper",
   "source": "[待核查]",
   "aliases": [
    "BA-ZSD",
    "Bansal ICCV 2019",
    "Background-Aware ZSD"
   ]
  },
  "AST_98d7c510": {
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   "type": "paper",
   "source": "https://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Ankan_Bansal_Zero-Shot_Object_Detection_ECCV_2018_paper.pdf",
   "aliases": [
    "Bansal ECCV 2018",
    "Zero-Shot Object Detection (Bansal)"
   ]
  },
  "AST_a9be7443": {
   "name": "Hayat-ZSD",
   "type": "package",
   "source": "https://github.com/nasir6/zero_shot_detection",
   "aliases": [
    "nasir6/zero_shot_detection",
    "Hayat Synthesizing Unseen"
   ]
  },
  "AST_28f3b6f5": {
   "name": "RRFS",
   "type": "package",
   "source": "https://github.com/HPL123/RRFS",
   "aliases": [
    "HPL123/RRFS",
    "Robust Region Feature Synthesizer"
   ]
  },
  "AST_cf2ef1a9": {
   "name": "GTNet",
   "type": "paper",
   "source": "https://arxiv.org/abs/2001.06812",
   "aliases": [
    "GTNet",
    "Generative Transfer Network",
    "arXiv:2001.06812"
   ]
  },
  "AST_6f89a8b7": {
   "name": "SAUI",
   "type": "paper",
   "source": "AAAI 2024 Vol 38",
   "aliases": [
    "Scale-Aware Unseen Imagineer",
    "SAUI AAAI 2024"
   ]
  },
  "AST_cf58600e": {
   "name": "DELO",
   "type": "paper",
   "source": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Zhu_Dont_Even_Look_Once_Synthesizing_Features_for_Zero-Shot_Detection_CVPR_2020_paper.pdf",
   "aliases": [
    "Don't Even Look Once",
    "Zhu CVPR 2020"
   ]
  },
  "AST_ad43c3db": {
   "name": "ZSD-YOLO",
   "type": "package",
   "source": "https://github.com/Johnathan-Xie/ZSD-YOLO",
   "aliases": [
    "Johnathan-Xie/ZSD-YOLO",
    "ZSD-YOLO ICDMW 2022"
   ]
  },
  "AST_1ff18dfa": {
   "name": "CLIP-YOLO",
   "type": "package",
   "source": "https://github.com/BJUTsipl/CLIP-YOLO",
   "aliases": [
    "BJUTsipl/CLIP-YOLO",
    "CLIP-YOLO 2025"
   ]
  }
 }
}