Unverified50% confidenceOpinionExact time
The author believes that the 'Chain-of-Thought' output of LLMs is more likely a highly fitted reproduction of reasoning patterns in training data, rather than genuine logical deduction in the true sense.
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50%
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Long-term
Relevance
10/2/2026
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Unverified思维链提示有效的原理是：LLM是逐词生成的自回归模型，先生成推理过程可作为后续推断的工作记忆，降低直接跳结论的错误率80% similarUnverifiedThe root cause of citation hallucination is that LLMs learn linguistic patterns by predicting the next word, and no factual database for real-time verification is embedded in the training process.76% similarVerifiedReasoning models perform internal Chain-of-Thought before returning final results, consuming large amounts of tokens and computation time in exchange for deeper understanding and lower error rates.76% similarUnverified在代码数据上训练的LLM不仅提升了编程能力，还显著增强了模型的逻辑推理能力，代码训练和逻辑推理能力之间存在正向迁移效应75% similar
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