Right Diagnoses, Decorative Reasoning:A Perturbation Audit of Medical Chain-of-Thought

Mengzhu Xu, Jifan Gao, Xia Jiang, Yaoxin Wu, Xi Long
8/25/2026
cs.AI

No official code found. Best implementation: dukexu619/medcot-audit (0 stars, last commit 2026-05-12).

Abstract

Clinicians read chain-of-thought (CoT) rationales as evidence of medical reasoning, but whether the visible chain plays that role is rarely tested. General-domain CoT-faithfulness probes ignore clinical cost, and medical LLM evaluations treat the chain as a black box. We close this gap with a medical perturbation audit: a 30-operator battery edits both the chain and the question with clinically motivated operators (severity reversal, negation flip, demographic swap, evidence ablation), paired with a chain-update times answer-flip joint analysis that classifies each model by its failure mode. Applied to 14 LLMs on four medical QA benchmarks, three independent tests converge: the Chain-Decoupling Rate (CDR; chain does not register the edit and the answer does not flip) is 72.9% panel-wide on clinically meaningful destructive edits, chain corruption leaves accuracy unchanged, and removing CoT prompting does not reduce accuracy. Two board-certified clinicians re-annotate N=197 perturbed questions; 98.5% leave the gold defensible. The pattern holds across medical and reasoning fine-tuning and scale; on the closed-source tier, where the chain text is unavailable, the answer-side signals are consistent with the same decoupling. Our framework and CDR provide a reusable yardstick for auditing whether medical CoT is faithful or merely documentation.

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Code Implementations(1)

A perturbation audit toolkit for medical chain-of-thought faithfulness

00May 12, 20265 months agoNOASSERTION

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Cite this paper

@article{xu2026right,
  title  = {Right Diagnoses, Decorative Reasoning:A Perturbation Audit of Medical Chain-of-Thought},
  author = {Mengzhu Xu and Jifan Gao and Xia Jiang and Yaoxin Wu and Xi Long},
  year   = {2026},
  eprint = {2608.24790},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2608.24790v1}
}

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