Chain-of-thought explanations in LLMs are frequently unfaithful: models systematically omit mention of biasing prompt features that change their answers and instead produce rationalizations for those biased outputs.
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Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting
Chain-of-thought explanations in LLMs are frequently unfaithful: models systematically omit mention of biasing prompt features that change their answers and instead produce rationalizations for those biased outputs.