Author

Yu Luo

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Preprint Oct 2026

PRISM: Precision Forcing for Generalist Vision-Language-Action Policies

Coupling a pretrained vision-language model (VLM) with a diffusion or flow-matching action expert has become the mainstream vision-language-action (VLA) paradigm for embodied policies, yet they remain unreliable once a task demands precise manipulation, e.g., submillimeter cable insertion. We attribute this weakness to...

Cheng-Hao Yue, Pei-Yan Li, Hao Wang et al. · 0 citations

Preprint Sep 2026

Beyond State-as-Action: Exploiting Command-State Discrepancy for Robot Imitation Learning

Constructing action targets from measured robot motion is an established approach in imitation learning. Under interaction constraints, however, command-state discrepancy may reflect control demands that motion alone does not capture. We investigate when this information matters and how to exploit it. Across three real...

Pei-Yan Li, Yue-Ran Tao, Enhao Zhang et al. · 0 citations

Open access Aug 2026

Embodied Learning under Policy and Dynamics Shifts

This work proposes Transition Occupancy Matching as a unifying principle to resolve policy and dynamics shifts within a single mathematical framework and introduces Occupancy-Matching Policy Optimization (OMPO), a novel algorithm that optimizes a surrogate objective explicitly correcting for transition discrepancies.

Yu Luo, Lei Lv, Fu-Chun Sun et al. · National Science Review · 0 citations