Author

Wen-Qiang Zhang

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Preprint Sep 2026

RoboFolDeX: A Physical-World Benchmark for Long-Horizon Robotic Manipulation of Deformable Objects

Embodied AI, including vision-language-action and world-action models, must operate reliably in the physical world. Yet methods that perform well in simulation can degrade substantially on real robots, especially in long-horizon deformable-object manipulation, where policies must track changing states and execute relia...

Chen-Huan Liu, Yi Xu, Feng Wu et al. · 0 citations

Preprint Jul 2026

EDAR: Learning Environment-Dependent Action Representations for Robotic Manipulation

Experiments on simulated and real-robot manipulation benchmarks demonstrate that EDAR improves downstream policy learning, especially in long-horizon manipulation, highlighting the importance of grounding action representations in executable control structure and environment-conditioned visual change.

Yuecheng Xu, Tong Yang, Jingkai Jia et al. · 0 citations