AI RESEARCH
Decoupling the Effect of Chain-of-Thought Reasoning: A Human Label Variation Perspective
arXiv CS.CL
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ArXi:2601.03154v2 Announce Type: replace Reasoning-tuned LLMs utilizing long Chain-of-Thought (CoT) excel at single-answer tasks, yet their ability to model Human Label Variation--which requires capturing probabilistic ambiguity rather than resolving it--remains underexplored. We investigate this through systematic disentanglement experiments on distribution-based tasks, employing Cross-CoT experiments to isolate the effect of reasoning text from intrinsic model priors.