Author

Shuang Chen

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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

#artificial intelligence Preprint Sep 2026

HIL-UMI: Bringing Human-in-the-Loop Post-Training of Vision-Language-Action Models to Universal Manipulation Interface

Large-scale vision-language-action (VLA) models provide powerful priors for robot manipulation, yet adapting them to a specific deployment remains challenging. Supervised fine-tuning (SFT) on task-specific demonstrations provides a step toward deployment, but faces two persistent limitations: static data provide limite...

Zimu Han, Yiming Zeng, Ji-Yao Zhang et al. · 0 citations