Author

Shuliang He

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Preprint Sep 2026

Praxis: Distilling Physical Interaction Priors from Egocentric Videos for Generalizable Whole-Body Manipulation

Mobile humanoid manipulation requires both reaching a usable workspace and preserving precise hand-object interactions as object poses and contact conditions change. Learning these behaviors from limited task-specific data remains challenging. To bridge this gap, we introduce Praxis, a whole-body manipulation framework...

Shu-Liang He, Rui-Yang Xu, Bo Yue et al. · 0 citations

Preprint Aug 2026

RoboReact: Agentic Skill Distillation from Generated Egocentric Videos for Generalizable Whole-Body Manipulation

This work presents RoboReact, a framework that automatically synthesizes whole-body humanoid manipulation skills from a single egocentric RGB-D observation, and highlights the potential of combining generative models, vision-language reasoning, and closed-loop control for scalable humanoid skill acquisition.

Shu-Liang He, Shuai Wang, Bo Yue et al. · 3 citations · ⚡1