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Jingkai Jia

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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