CodeActionBench: Evaluating Agentic Code-as-Policy for Embodied Manipulation
cs.RO, cs.AI
Submitted: 2026-09-27
Updated: 2026-09-27
Code: https://github.com/openai/codex
Terminology
Sources
- SAM 3: Segment Anything with Concepts
- RoboScript: Code Generation for Free-Form Manipulation Tasks across Real and Simulation
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- ETA: A New Agentic Paradigm for Embodied Tasks
- CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation
- Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model
- Kimi K3: Open Frontier Intelligence
- DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation
- From Fixed to Free Cameras: Calibration-Free View-Robust Vision-Language-Action Model
- Evaluating Real-World Robot Manipulation Policies in Simulation
- Being-H0.5: Scaling Human-Centric Robot Learning for Cross-Embodiment Generalization
- Robotic Long-Horizon Manipulation with Progressive In-Context Code Generation and Episodic Feedback
- G$^3$VLA: Geometric inductive bias for Vision-Language-Action Models
- cuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation
- In-Context VLA: Endowing Vision-Language-Action Models with Language via In-Context Post-Training and Agentic Tool Use
- GeoProp: Grounding Robot State in Vision for Generalist Manipulation
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- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving