Extrinsic Hallucinations in LLMs
lilianweng.github.io- Category
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- @lilianweng
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- Jul 21, 2026
About
Hallucination in large language models usually refers to the model generating unfaithful, fabricated, inconsistent, or nonsensical content. As a term, hallucination has been somewhat generalized to cases when the model makes mistakes. Here, I would like to narrow down the problem of hallucination to cases where the model output is fabricated and not grounded by either the provided context or world knowledge. There are two types of hallucination: In-context hallucination: The model output should
Why it made the leaderboard
It gives a precise taxonomy of hallucination (in-context vs. extrinsic) and surveys the actual detection and mitigation methods, so you can design evals and factuality guardrails around what your model genuinely doesn't know versus what it fabricates.
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