ω → 0 . 6 : a VLA That Learns From Experience Physical
Ali Amin, Raichelle Aniceto, Ashwin Balakrishna et al.
· 0 citations
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Jul 2026
Sample-Efficient Learning from Agent Experience
Compared with classical reinforcement-learning baselines, in-context learning from trial-and-error experience followed by Experience Distillation matches their performance with at least \(9.6\times\) fewer environment samples.
Chenhui Gou, Haoqin Tu, Yun-Hao Fang et al.
· arXiv.org · 0 citations
Preprint
Aug 2026
Chain-of-Experience for Continual LLM Improvement
This study studies how LLMs learn from iterative experience at test time, a setting the authors refer to as Chain-of-Experience (CoE), where models accumulate experiential traces through iterative interactions with self or environmental feedback to form a continual improvement loop beyond zero-shot inference.
Hao-Qin Tu, Yun-Hao Fang, Yizhong Wang et al.
· 0 citations