AINeutralarXiv – CS AI · 6h ago6/10
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Skill Reuse as Compression in Agentic RL
Researchers introduce ReuseRL, a reinforcement learning framework that improves LLM agent generalization by encouraging skill reuse and compression. By grounding agentic RL in the Minimum Description Length principle and penalizing task-specific shortcuts, the method demonstrates better in- and out-of-distribution performance across multiple benchmark environments.