Author

Peidong Liu

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Preprint Sep 2026

DexWeave: Learning Dexterous Humanoid Loco-Manipulation from Human Demonstrations

Learning dexterous humanoid loco-manipulation from human demonstrations requires transferring not only human motion, but also the coordinated interaction structure underlying the demonstrated behavior. This is challenging because embodiment differences distort the coupling among body motion, wrist placement, finger art...

Nai-Chuan Sun, Hao Shen, Yi-Zhang Zhang et al. · 0 citations

Preprint Aug 2026

WorldSimProbe: Diagnosing Simulator Faithfulness in Action-Conditioned World Models for Embodied Manipulation

This work formalizes Observable Simulator Contract, a minimal contract that any action-conditioned physical simulator should satisfy: supplied actions must induce corresponding agent motion, and environment responses must be grounded in that realized motion.

P. Co, Sichen Hu, Chun-Xuan Jiao et al. · 1 citation

Preprint Aug 2026

Beyond Flat Policies: Hierarchical Post-Training for Embodied Agents in Robotic Manipulation

Hierarchical Robotic Control (HiRoC) is proposed, a hierarchical post-training framework that decouples high-level task planning from low-level action execution and aligns the executor with planner-generated subgoals before reinforcement learning, mitigating the distribution misalignment between planning and execution.

He Kong, Ze Chen, Qi Wang et al. · 0 citations