Expired70% confidenceFactExact time
Large language models have hallucination problems and may fabricate non-existent references, invent experimental data, or provide incorrect statistical figures.
4
Sources
70%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 9/30/2026(expired)
Sources
Related Claims
UnverifiedLarge language models still face hallucination problems in information extraction tasks, potentially completing information not explicitly mentioned in conversations and causing inaccurate CRM data.80% similarUnverifiedThe biggest risk of large models in data analysis scenarios is fabricating seemingly plausible but actually incorrect data when the corresponding field cannot be found.76% similarUnverified低质量的知识库会导致幻觉式引用,即模型看似使用知识库内容实则引用了错误或无关片段75% similarUnverifiedLarge language models may generate content that appears credible but is completely wrong (hallucinations), thereby misleading users' decisions.72% similarUnverifiedAbsence verification requires the model to actively infer which important information that should have appeared in the source material was omitted, necessitating the prior construction of a complete mental model of what ought to be present, which is far more difficult for LLMs.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/45479API
curl https://kongchang.com/api/v1/knowledge/claims/45479MCP
get_claim(id=45479)