AI RESEARCH
Characterizing, Evaluating, and Optimizing Complex Reasoning
arXiv CS.CL
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ArXi:2602.08498v2 Announce Type: replace Large Reasoning Models (LRMs) increasingly rely on reasoning traces with complex internal structures. However, existing work lacks a unified answer to three fundamental questions: (1) what defines high-quality reasoning, (2) how to reliably evaluate long, implicitly structured reasoning traces, and (3) how to use such evaluation signals for reasoning optimization. To address these challenges, we provide a unified perspective. (1) We