Qiang Liu
2 indexed papers
Recent (6 mo)
2With code
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0Publications per year
226
Top categories
AI×1NLP×1
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Research Timeline
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.
CRAFTQA: A Code-Driven Adaptive Framework for Complex Structured Data Reasoning
CRAFTQA introduces a novel adaptive, code-driven framework that significantly enhances complex structured data reasoning by dynamically generating custom code functions beyond predefined operations.
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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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cs.CLRecentJun 1, 2026