AI RESEARCH
Entropy-Gradient Inversion: Moving Toward Internal Mechanism of Large Reasoning Models
arXiv CS.CL
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ArXi:2605.17770v1 Announce Type: cross The advancement of Large Reasoning Models (LRMs) has catalyzed a paradigm shift from reactive ``fast thinking'' text generation to systematic, step-by-step ``slow thinking'' reasoning, unlocking state-of-the-art performance in complex mathematical and logical tasks. However, the field faces \textit{the fundamental gap between token-level behavioral analysis and internal reasoning mechanisms, and the instability of reinforcement learning (RL) for reasoning optimization relying on costly external verifiers