AI RESEARCH
Beyond Benchmarks: Dynamic, Automatic And Systematic Red-Teaming Agents For Trustworthy Medical Language Models
arXiv CS.LG
•
ArXi:2508.00923v2 Announce Type: replace Ensuring the safety and reliability of large language models (LLMs) in clinical practice is critical to prevent patient harm. However, LLMs are advancing so rapidly that static benchmarks quickly become obsolete or prone to overfitting, yielding a misleading picture of model trustworthiness. Here we