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In the field of explainable AI, faithfulness is regarded as a core requirement for explanation quality: an explanation must accurately reflect the model's true behavior.
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11/5/2026
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UnverifiedAI confidently expressing agreement does not equal independent verification; the model may echo the user's claims.73% similarUnverifiedThe paper proposes that faithfulness should be understood as a joint relation between model and explanation, but this relation is not fully specified.73% similarUnverifiedChain-of-thought output may simply be a rationalization output pattern learned by the model, not fully corresponding to the actual internal information processing path—a phenomenon referred to in AI interpretability research as the 'faithfulness problem'.73% similarUnverified主动要求AI引入可信瑕疵可以对抗模型的讨好性偏差，从而提升输出的真实度72% similarUnverifiedThe author proposes that AI trust should follow three principles: trust must be verifiable, conservative failure is preferable to aggressive correctness, and continuous monitoring is required rather than one-time verification.72% similar
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