Unverified60% confidenceFactExact time
Native large models suffer from a knowledge cutoff problem and will produce hallucinations when answering questions about content after their training date.
2
Sources
60%
Confidence
Long-term
Relevance
9/17/2026
First Seen
Sources
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Related Claims
VerifiedThe content returned by large models is essentially data from the point in time when they were trained, with a definitive knowledge cutoff.79% similarVerified大模型幻觉的技术本质在于模型在训练时学习的是语言模式的概率分布而非事实本身75% similarUnverifiedNative large models are trained on publicly available data, have no independent reasoning ability, can only perform probabilistic generation based on learned knowledge, and have a knowledge cutoff date.75% similarUnverifiedKnowledge stored in large model parameters has a cutoff date and is prone to hallucination—generating content that appears plausible but is actually incorrect.73% similarVerifiedThe knowledge of traditional language models comes entirely from training data, with a hard limitation of a knowledge cutoff date, making it impossible to perceive events that occurred after training was completed.73% similar
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