Unverified60% confidenceFactTime unknown
Large language models generate fabricated content (hallucinations) with high confidence, including inventing non-existent tool names and forging API return results
2
Sources
60%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe hallucination problem in large language models can lead to the generation of fabricated references that have the correct format but cannot be found in real databases.78% similarVerifiedLarge language models have hallucination defects in code generation scenarios, manifested as referencing non-existent library functions and generating syntactically correct but logically erroneous code.76% similarUnverified大型语言模型可生成个性化钓鱼邮件，AI 图像生成工具如 Stable Diffusion、Midjourney 可批量生成逼真人物头像，使虚假身份更难识别75% similarVerifiedThe root cause of hallucinations in large language models lies in the Transformer architecture's objective of maximizing probability during text generation, rather than prioritizing factual accuracy.75% similarUnverifiedFakeSpotter uses a technical implementation combining repeated large language model evaluation with domain-specific logistic regression classifiers.75% similar
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