mlsanityData to 7 Oct 2026

Decoupling the Effect of Chain-of-Thought Reasoning: A Human Label Variation Perspective

arXiv 2601.03154 ↗First posted 6 Jan 2026cs.CLcited by 6

On the map: LLM reasoning → Prompting and chain-of-thought reasoning

Abstract (arXiv)

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. We observe a distinct "decoupled mechanism": while CoT improves distributional alignment, final accuracy is dictated by CoT content (99% variance contribution), whereas distributional ranking is governed by model priors (over 80%). Step-wise analysis further shows that while CoT's influence on accuracy grows monotonically during the reasoning process, distributional structure is largely determined by LLM's intrinsic priors. These findings suggest that long CoT serves as a decisive LLM decision-maker for the top option but fails to function as a granular distribution calibrator for ambiguous tasks.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 20 of its 51 references that are in the map. First posted on arXiv 6 Jan 2026.

Builds on

20 of 51 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025Early Stopping Chain-of-thoughts in Large Language Models17 Sep
  2. 2025Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens2 Aug

Other references · 18

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2024The Llama 3 Herd of Modelscited by 14,192
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  4. 2025Qwen3 Technical Reportcited by 8,195
  5. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  6. 2024GPT-4o System Cardcited by 4,467
  7. 2023GPQA: A Graduate-Level Google-Proof Q&A Benchmarkcited by 2,748
  8. 2025gpt-oss-120b & gpt-oss-20b Model Cardcited by 1,258
  9. 2024ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Toolscited by 1,096
  10. 2023Towards Measuring the Representation of Subjective Global Opinions in Language Modelscited by 424
  11. 2025Olmo 3cited by 95
  12. 2025Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Modelscited by 65
6 more
  1. 2025Reasoning Models Better Express Their Confidencecited by 63
  2. 2025SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviorscited by 48
  3. 2025Temporalizing Confidence: Evaluation of Chain-of-Thought Reasoning with Signal Temporal Logiccited by 11
  4. 2025Can Reasoning Help Large Language Models Capture Human Annotator Disagreement?cited by 9
  5. 2025Training and Evaluating with Human Label Variation: An Empirical Studycited by 8
  6. 2025Agree, Disagree, Explain: Decomposing Human Label Variation in NLI through the Lens of Explanationscited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026Value of Information: A Framework for Human-Agent Communicationcited by 10
  2. 2026Steer Model beyond Assistant: Controlling System Prompt Strength via Contrastive Decodingcited by 1
  3. 2026Reasoning Models Know What's Important, and Encode It in Their Activationscited by 1
  4. 2026Annotation Entropy Predicts Per-Example Learning Dynamics in LoRA Fine-Tuningcited by 0
  5. 2026Human Label Variation as Stable Signal: Learning Annotator-Specific Explanation Behavior via Cross-Annotator Preference Optimizationcited by 0
  6. 2026Reasoning that Travels: Dissecting How Chain-of-Thought Transfers Across Modelscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Does Verbose Chain-of-Thought Really Help? In-Distribution Evidence that Content, Not Length, Matters
  2. 2025Threading the Needle: Reweaving Chain-of-Thought Reasoning to Explain Human Label Variation
  3. 2026Legibility is Not Interpretability: Comparing Judged and Actual Importance in Chain-Of-Thought Reasoning
  4. 2025Chain-of-Thought as a Lens: Evaluating Structured Reasoning Alignment between Human Preferences and Large Language Models
  5. 2024Fine-Tuning on Diverse Reasoning Chains Drives Within-Inference CoT Refinement in LLMs
  6. 2026LLM Reasoning Is Latent, Not the Chain of Thought
  7. 2025Rethinking the Chain-of-Thought: The Roles of In-Context Learning and Pre-trained Priors
  8. 2023Measuring Faithfulness in Chain-of-Thought Reasoning