Verified65% confidenceFactExact time
Large language models rely solely on parameter weights fixed during training for autoregressive generation at inference time, and have two inherent limitations: a knowledge cutoff and capability boundaries
3
Sources
65%
Confidence
Long-term
Relevance
7/17/2026
First Seen
Sources
Related Claims
VerifiedThe 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.80% similarUnverifiedThe parameter count of traditional large language models is fixed once training is complete, and the model's knowledge is frozen in the weight matrices79% similarPartially Verified大语言模型生成代码的底层机制是基于海量训练语料的条件概率预测，模型并不真正理解代码逻辑78% similar
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