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Counterfactual Tests for Measuring Chain-of-Thought Faithfulness in Visual Language Models

arXiv · AI, language, vision and robotics · article · Sep 6, 2026 · UTC

Chain-of-thought (CoT) may often look plausible, yet it may not faithfully reflect the model's decision-making process. While methods for measuring the faithfulness of CoTs for textual inputs have been increasingly introduced, using these methods for visual inputs is not straightforward. In this work, we adapt the family of counterfactual methods for measuring CoT faithfulness, namely the Counterfactual Test (CT) and Correlational Counterfactual Test (CCT), to visual inputs, and call them vCT and vCCT, respectively. Using vCT and vCCT, we benchmark eight recent open-source Vision Language Mode

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Evidence & attribution

First collected: 2026-09-20T21:12:06.801Z. This is not the publication date.