Unverified50% confidenceFactExact time
The knowledge boundary of a general-purpose large model is determined by its training data, so it cannot answer questions related to non-public data such as internal enterprise documents, product prices, and customer information.
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Long-term
Relevance
10/29/2026
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Related Claims
UnverifiedWhen a model fails to correctly invoke retrieval tools or determines that a question does not require a search, it falls back to answering from training data, thereby exposing the knowledge cutoff issue.75% similarVerifiedA model's knowledge is frozen in the parameter weights at training time and cannot perceive the current time or access real-time data; this is known as the knowledge cutoff problem.74% similarUnverifiedIn LLM projects, data simultaneously plays three roles: training corpus, retrieval knowledge base, and runtime context, and the three have inconsistent requirements for data.73% similarUnverifiedThe root cause of poor knowledge base performance typically lies in unreasonable document chunking strategies, inappropriate vector model selection, or insufficient retrieval recall quantity, rather than issues with the model itself.70% similar
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