Verified70% confidenceFactExact time
Pre-training data for large models has a clear cutoff date, the model internally contains no enterprise private data, and hallucinations occur when directly queried about enterprise private information.
4
Sources
70%
Confidence
Long-term
Relevance
7/22/2026
First Seen
Sources
Related Claims
UnverifiedOnce false information is incorporated into a model's training data, it is very difficult to completely remove it from an already trained model even if it is subsequently debunked.75% similarUnverifiedRAG can supplement knowledge beyond the training data cutoff date in real time, avoiding expensive full fine-tuning of the model.74% similarUnverifiedTraditional large model training relies heavily on manually annotated data and external corpus collection, which are typically the bottlenecks constraining iteration speed.73% similarPartially VerifiedA pre-trained model refers to a model that has been trained in advance on large-scale datasets, which users can directly fine-tune or call to complete specific tasks.73% similarUnverifiedMainstream benchmark problems have been widely discussed on the internet, and models' training data may contain memorization of these problems, causing benchmark scores to overestimate the models' capabilities on truly unseen tasks73% similar
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