A phenomenon where LLMs generate plausible-sounding but factually incorrect or fabricated information, often with high confidence.
When the AI makes something up and says it like it's true, even though it's not — like telling a really convincing fib.
When an AI confidently gives you wrong information — it sounds right but it just made it up. That's why you should double-check important facts.
A phenomenon where LLMs generate plausible-sounding but factually incorrect or fabricated information, often with high confidence.
The generation of content that is syntactically fluent but semantically unfaithful to source data or world knowledge, arising from the model's tendency to optimize for fluency over factual accuracy.
Unfaithful generation where the model's output diverges from the grounding context or world model — categorized as intrinsic (contradicting the source) or extrinsic (unverifiable), driven by exposure bias, knowledge conflicts, and decoding dynamics.
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