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cs.AI2026
Model-Adaptive Tool Necessity Reveals the Knowing-Doing Gap in LLM Tool Use
Yize Cheng, Chenrui Fan, Mahdi JafariRaviz +2
Large language models (LLMs) increasingly act as autonomous agents that must decide when to answer directly vs. when to invoke external tools. Prior work studying adaptive tool use…
cs.AI2025
Understanding the Thinking Process of Reasoning Models: A Perspective from Schoenfeld's Episode Theory
Ming Li, Nan Zhang, Chenrui Fan +6
While Large Reasoning Models (LRMs) generate extensive chain-of-thought reasoning, we lack a principled framework for understanding how these thoughts are structured. In this paper…
cs.AI2025
Missing Premise exacerbates Overthinking: Are Reasoning Models losing Critical Thinking Skill?
Chenrui Fan, Ming Li, Lichao Sun +1
We find that the response length of reasoning LLMs, whether trained by reinforcement learning or supervised learning, drastically increases for ill-posed questions with missing pre…