Vision-Language-Action (VLA) models have shown strong promise for general-purpose robotic manipulation, but existing approaches often condition control on entangled multimodal features that do not explicitly preserve task-relevant structure during action generation. This limitation is especially pronounced in long-hori...
Pei-Sen Huang, Jian-Hua Hu, Jie-Ren Deng et al.· 2026 IEEE 22nd International...· 0 citations
Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, yet pretrained policies do not always expose the information needed for precise action generation. In particular, effective control can benefit from (i) temporal context that reflects how recent actions have shaped the current sce...
Pei-Sen Huang, Jian-Hua Hu, Jie-Ren Deng et al.· 2026 IEEE 22nd International...· 0 citations
Reinforcement learning can substantially improve a reasoning teacher, but it is unclear which of those improvements survive when the teacher supervises a smaller on-policy student. We study this question in mathematical reasoning by comparing teacher lineages before and after GRPO, multiple student scales, direct GRPO,...
Xiao-Yu Chen, Bo Shao, Tian-Gang Zhu et al.· 0 citations
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