Concept
Faithfulness Hallucination
The phenomenon in which a large model's answer appears plausible but deviates from the user's instructions or the input context. Its root cause lies in insufficient instruction-following capability of the model, which requires improvement through fine-tuning or RLHF.
Timeline (last 90 days)
Sep 8
Academia divides AI hallucinations into two broad categories: faithfulness hallucinations (output inconsistent with the given source input) and factuality hallucinations (output contradicting verifiable world knowledge).
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