Author

Linfeng Zhang

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Preprint Sep 2026

Dense to MoE Adaptation for Compact Vision Language Action Policies

Vision language action (VLA) policies continue to grow in parameter count, making deployment on resource-constrained robot platforms difficult. The central goal is to reduce the number of LLM-side parameters retained in the deployed policy while preserving downstream task performance. Our approach, AdaDE, adapts select...

Mu-Chun Niu, Shuang Chen, Yu-Zhou Wu et al. · 0 citations

Jul 2026

Reducing Temporal Redundancy for Efficient Vision-Language-Action Inference

A system level acceleration strategy that reduces computation in both perception and action generation and compress diffusion sampling into a compact 2-step schedule through efficiency oriented training while preserving action precision is proposed.

Yuzhou Wu, Yuxin Zheng, Muchun Niu et al. · arXiv.org · 0 citations