MovieGrid, a Multi-Grid Post-Training paradigm that decomposes a long video into shorter, temporally ordered chunks and arranges them on a spatial grid for joint modeling, is proposed, reducing the number of shots handled by each temporal axis while enabling global information exchange across chunks.
Jia-Wei Mao, Hao-Qin Tu, Hardy Chen et al.· 0 citations
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.
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
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