Dianxing Tang
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126
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2026
Learning When Not to Act: Mitigating Tool Abuse in Agentic Reinforcement Learning
The paper proposes EAPO, a framework that enables agentic models to learn when to forgo using external tools, thereby mitigating tool abuse while maintaining high reasoning accuracy.
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Papers
cs.AIRecentJun 1, 2026
Learning When Not to Act: Mitigating Tool Abuse in Agentic Reinforcement Learning
Liuji Chen, Dianxing Tang, Xing Shi, Dingshuo Chen +3 more
The paper proposes EAPO, a framework that enables agentic models to learn when to forgo using external tools, thereby mitigating tool abuse while maintaining high reasoning accuracy.
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