2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CL2025
MedFactEval and MedAgentBrief: A Framework and Workflow for Generating and Evaluating Factual Clinical Summaries
François Grolleau, Emily Alsentzer, Timothy Keyes +17
Evaluating factual accuracy in Large Language Model (LLM)-generated clinical text is a critical barrier to adoption, as expert review is unscalable for the continuous quality assur…
cs.AI2025★ 2 cited
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records
Philip Chung, Akshay Swaminathan, Alex J. Goodell +26
Methods to ensure factual accuracy of text generated by large language models (LLM) in clinical medicine are lacking. VeriFact is an artificial intelligence system that combines re…