Author

Mu-Tian Xu

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Preprint Oct 2026

DeXplicit: Making Physical State Explicit in Dexterous Manipulation World Models

Before acting on an object, a robot needs to anticipate how its hand motion will change the physical world and what the resulting scene will look like. Existing approaches typically entangle action-conditioned dynamics, camera motion, and visual synthesis within a video generation model, or represent dynamics as point...

Adam Lee, Mu-Tian Xu, Yu-Kang Cao et al. · 0 citations

Preprint Sep 2026

CosmoH2G: A Hand-to-Gripper Transfer Dataset and Baseline Method for Object Manipulation with Complex Spatial Movements

A scalable acquisition pipeline to collect hand-gripper paired demonstrations is introduced, governed by a rigorous protocol that prioritizes motion complexity and leverages a handheld gripper for seamless action mimicry, and enables stable and precise hand-to-gripper transfer of complex spatial manipulations.

Hong-Xia Zhao, Mu-Tian Xu, Ze-Yu Jin et al. · 0 citations