Edward Duan — accepted AI-conference papers

2026

X-Diffusion: Training Diffusion Policies on Cross-Embodiment Human Demonstrations

Maximus Pace, Prithwish Dan, Chuanruo Ning, Atiksh Bhardwaj, Moyun Du, Edward Duan +2

ICRA 2026poster

Human videos are a scalable source of training data for robot learning. However, humans and robots significantly differ in embodiment, making many human actions infeasible for direct execution on a robot. Still, these demonstrations convey rich object-interaction cues and task intent. Our goal is to…

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2025

X-Sim: Cross-Embodiment Learning via Real-to-Sim-to-Real

Prithwish Dan, Kushal Kedia, Angela Chao, Edward Duan, Maximus Adrian Pace, Wei-Chiu Ma +1

CoRL 2025oral

Human videos offer a scalable way to train robot manipulation policies, but lack the action labels needed by standard imitation learning algorithms. Existing cross-embodiment approaches try to map human motion to robot actions, but often fail when the embodiments differ significantly. We propose X-S…

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