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News/Skill Reuse as Compression in Agentic RL
arxiv
PublishedSeptember 2, 2026 at 4:00 AM
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Skill Reuse as Compression in Agentic RL

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arXiv:2605.31509v2 Announce Type: replace-cross Abstract: Large language model agents trained with reinforcement learning (RL) often learn brittle, task-specific shortcuts. We hypothesize that agents generalize better when their successful trajectories are structurally compressible, decomposed into

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