[KongchangAI]
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).

Unverified50%

All Facts (1)

Source Articles