Unverified50% confidenceFactExact time
A large model's knowledge is frozen at the point in time when training was completed, and it has no knowledge of new events that occurred after training.
1
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50%
Confidence
Long-term
Relevance
10/1/2026
First Seen
Sources
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Related Claims
VerifiedCurrent large models are essentially static—once training is complete, the weights are frozen and knowledge remains at the training cutoff date.75% similarUnverifiedAfter current large models complete training, their weights are frozen, and they simulate awareness of new information through context windows and RAG, while the model itself does not truly change.72% similarUnverifiedAs the scale of pretrained models increases, many previously effective explicit knowledge injection techniques have gradually become ineffective or even produced negative effects.72% similarUnverifiedThe core pain point that Function Calling addresses is that large models enter a state of knowledge stagnation after training ends and cannot obtain new information after the training cutoff.71% similarVerifiedLarge language models have a knowledge cutoff in their training data, meaning they only possess information available before the training cutoff date.70% similar
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