AI RESEARCH
VeriLLMed: Interactive Visual Debugging of Medical Large Language Models with Knowledge Graphs
arXiv CS.CL
•
ArXi:2604.23356v1 Announce Type: new Large language models (LLMs) show promise in medical diagnosis, but real-world deployment remains challenging due to high-stakes clinical decisions and imperfect reasoning reliability. As a result, careful inspection of model behavior is essential for assessing whether diagnostic reasoning is reliable and clinically grounded. However, debugging medical LLMs remains difficult. First, developers often lack sufficient medical domain expertise to interpret model errors in clinically meaningful terms.