CoT并非真正推理，而是强制模型模仿思考过程的结构约束。
CoT is Not True Reasoning, It Is Just a Tight Constraint to Imitate: A Theory Perspective
- 用中间步骤约束模型输出，使其模仿推理形式
- 提升多步任务表现，但非源于真实抽象推理
- 适合质疑模型推理能力本质的研究者阅读
链式思维（Chain-of-Thought, CoT）提示显著提升了大语言模型在多步推理任务上的表现，引发关于模型具备涌现推理能力的广泛讨论。本文从理论视角提出反观点：CoT并未激发真正的抽象推理能力。相反，它作为一种强大的结构约束，引导大语言模型模仿推理形式。通过强制生成中间步骤，CoT利用模型在序列预测和模式匹配上的强大能力，将输出限制在看似连贯的思维序列中。这一机制并非产生深层逻辑推理，而是通过结构化输出模仿推理表象。
原文摘要 · Abstract (English)
Chain-of-Thought (CoT) prompting has demonstrably enhanced the performance of Large Language Models on tasks requiring multi-step inference. This success has led to widespread claims of emergent reasoning capabilities in these models. In this paper, we present a theoretical counter-perspective: Chain-of-Thought (CoT) does not elicit genuine, abstract reasoning. Instead, we argue that Chain-of-Thought functions as a powerful structural constraint that guides Large Language Models to imitate the form of reasoning. By forcing the generation of intermediate steps, Chain-of-Thought leverages the model immense capacity for sequence prediction and pattern matching, effectively constraining its output to sequences that resemble coherent thought processes. Chain-of-Thought (CoT) prompting has demonstrably enhanced the performance of Large Language Models on tasks requiring multi-step inference. This success has led to widespread claims of emergent reasoning capabilities in these models. In this paper, we present a theoretical counter-perspective: Chain-of-Thought (CoT) does not elicit genuine, abstract reasoning. Instead, we argue that Chain-of-Thought functions as a powerful structural constraint that guides Large Language Models to imitate the form of reasoning. By forcing the generation of intermediate steps, Chain-of-Thought leverages the model immense capacity for sequence prediction and pattern matching, effectively constraining its output to sequences that resemble coherent thought processes.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。