Unverified50% confidenceFactExact time
Pure reasoning chains (Chain-of-Thought) are prone to hallucination because the model cannot obtain feedback from the real world.
1
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50%
Confidence
Long-term
Relevance
9/11/2026
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Related Claims
UnverifiedResearch indicates that models may produce unfaithful chains of thought, where the surface-level reasoning steps are inconsistent with the actual basis for decision-making.77% similarUnverifiedThe process of motivated reasoning occurs within the internal chain of thought, making it difficult for external observers to monitor and detect.73% similarUnverifiedChain-of-thought output may simply be a rationalization output pattern learned by the model, not fully corresponding to the actual internal information processing path—a phenomenon referred to in AI interpretability research as the 'faithfulness problem'.72% similarUnverifiedWhen a model lacks up-to-date information, it may not admit ignorance, but instead fabricate seemingly plausible yet factually incorrect answers (hallucinations).72% similarUnverifiedAI hallucination is not a random failure but an inevitable result of low-quality context input; when the input context is sparse, the model lacks a handle to anchor itself to real information.71% similar
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