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Measuring Faithfulness Depends on How You Measure: Classifier Sensitivity in LLM Chain-of-Thought Evaluation

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Measured hint-verbalization rates in chain-of-thought faithfulness evaluations depend heavily on the LLM judge used.
Supports. The study compares three classifiers on the same 10,276 traces, only one of which is a standalone LLM judge; the largest gaps arise between a lenient mention-based pipeline and a stricter dependence-based judge, so the spread reflects judge prompt and construct as well as judge model. No human-labelled ground truth is used. Oct 30, 2026

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On identical data, these classifiers produce overall faithfulness rates of 74.4%, 82.6%, and 69.7%, respectively. Per-model gaps range from 2.6 to 30.6 percentage points.

Measured hint-verbalization rates in chain-of-thought faithfulness evaluations depend heavily on the LLM judge used.SupportedReading · this claim’s Steward

Supports. The study compares three classifiers on the same 10,276 traces, only one of which is a standalone LLM judge; the largest gaps arise between a lenient mention-based pipeline and a stricter dependence-based judge, so the spread reflects judge prompt and construct as well as judge model. No human-labelled ground truth is used.

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Link: https://arxiv.org/html/2603.20172
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Oct 30, 2026ReadingSteward of “Measured hint-verbalization rates in chain-of-t…” · supports, read whole
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