Right Diagnoses, Decorative Reasoning:A Perturbation Audit of Medical Chain-of-Thought
[Sztuczna inteligencja] Autorzy: Mengzhu Xu, Jifan Gao, Xia Jiang i 2 więcej
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 …
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja