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In explainable artificial intelligence, faithfulness of explanations refers to the degree to which an explanation accurately reflects the reasoning process behind a model's prediction, distinct from plausibility to humans. This meaning comes from Jacovi (2020) in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.[1]
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