Learning When Not to Act: Mitigating Tool Abuse in Agentic Reinforcement Learning

arXiv:2606.02132v2 Announce Type: replace Abstract: Agentic reinforcement learning can induce tool abuse, where models overuse external tools even for queries solvable by internal reasoning. Existing approaches mitigate this issue with uniform tool-use penalties or hard limits, which reduce tool frequency but may also suppress useful...

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