Unverified50% confidenceFactExact time
丰富的上下文信息能收窄模型输出概率分布并减少幻觉，这一现象被称为「知识锚定效应」
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50%
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Long-term
Relevance
7/18/2026
First Seen
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Related Claims
UnverifiedBy injecting large amounts of domain expertise into the model, fine-tuning can significantly reduce the hallucination rate in specific scenarios83% similarUnverifiedReasoning capabilities can be compressed through knowledge distillation and reinforcement learning fine-tuning, but the storage of factual knowledge depends on parameter scale, and compression leads to reduced knowledge coverage and higher hallucination rates.83% similarUnverifiedResearch shows that hallucination rate is negatively correlated with the knowledge density of the prompt; the richer and more precise the context provided in the prompt, the lower the probability that the model will generate fabricated content.83% similarUnverified规模缩放定律研究表明，增大模型参数量能提升常见知识准确性，但对长尾事实的改善边际效益递减77% similar
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