A Multi-Domain Red Teaming Framework for Safety, Robustness, and Fairness Evaluation of Medical Large Language Models

In three linesMulti-domain red teaming framework evaluating 11 LLMs across 690 clinical scenarios. Results: substantial variance (scores 0.791–0.984), safety-critical failures masked by aggregate accuracy, 10-20% error amplification on equity tasks. Hybrid evaluation (automated + human validation) essential.

Summary generated by Claude — human-verified