Unverified50% confidenceFactExact time
自回归机制决定了模型无法回头修改已生成的内容，这也解释了为何幻觉一旦出现会在后续文本中被延续
1
Sources
50%
Confidence
Long-term
Relevance
8/12/2026
First Seen
Sources
Related Claims
UnverifiedA model's commitments and memory writes do not change its underlying probability distribution, and its reflection is essentially just generating text that fits conversational expectations rather than truly updating behavioral strategies, so it may repeat the same mistakes.74% similarUnverified提示词中早期出现的词汇因串行依赖结构对后续生成具有不成比例的决定性影响，模型无法回头修正73% similarUnverifiedHallucinations stem from the model's optimization objective itself—the model is trained to generate linguistically coherent and statistically plausible continuations, not factually accurate answers.73% similarUnverifiedModel hallucination refers to models generating outputs that appear plausible but are actually incorrect, requiring robust rollback, retry, and human intervention mechanisms to address.72% similarVerifiedThe technical root cause of hallucination in large models lies in the autoregressive generation mechanism, where the model predicts only the statistically most likely next token based on the preceding context; researchers divide hallucinations into intrinsic hallucinations and extrinsic hallucinations.71% similar
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