Unverified50% confidenceFactExact time
Language models generate text based on probability, and tend to output generic praise, generalized emotional expressions, or plausible-sounding details that did not actually happen, the so-called "false memories".
1
Sources
50%
Confidence
Long-term
Relevance
10/13/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe reason large language models fabricate references is that they generate text based on probability rather than database retrieval, a phenomenon known as AI hallucination.78% similarVerifiedThe output of large language models is fundamentally probabilistic text generation, and a single rephrasing of a prompt can change field names, nesting levels, or enumeration values in the output without triggering compile-time or static analysis warnings.76% similarUnverifiedWhen a large language model generates text, each word is sampled from a probability distribution, and there are many equivalent alternatives between high-probability and low-probability words, providing space for watermark injection.74% similarUnverified大语言模型在生成查找目标文本时依赖记忆重建而非逐字符复制,在长上下文场景下会出现记忆漂移导致字符串替换静默失败,此现象被称为幻觉性精确74% 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.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1013652API
curl https://kongchang.com/api/v1/knowledge/claims/1013652MCP
get_claim(id=1013652)