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Robotics
Learning-based control of physical systems — manipulation, locomotion, vision-language-action models, and simulation-to-real transfer for autonomous robots.
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Show-Harness: Just a VLM Agent Can Play Robots
Agents · Sep 9 · 10:04
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SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators
Reinforcement Learning · Sep 8
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CosmoH2G: A Hand-to-Gripper Transfer Dataset and Baseline Method for Object Manipulation with Complex Spatial Movements
Agents · Sep 7
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DriveZero: End-to-End Driving Beyond Human Demonstrations
Reinforcement Learning · Sep 5
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Three Independent Reasons a Robot Success Rate Can Mislead You
Evaluation · Sep 5 · 12:09
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GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation
Inference Optimization · Sep 4
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RoboTok: An Internet-Scale Data Engine for Human Demonstration Retrieval and Dexterous Manipulation Learning
RAG · Sep 2
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Evaluating Multimodal LLMs as Generalist Vision-Language-Action Agents for Drone Control: Commanding, Approaching, Tracking and Searching
Agents · Sep 1
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ZimaBlue: Evolving Generalizable World Action Models through Scalable Video Pre-training
Inference Optimization · Aug 31 · 7:40
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Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
Multimodal · Aug 27 · 7:08
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