M-Eval: A Heterogeneity-Based Framework for Multi-evidence Validation in Medical RAG Systems
NeutralArtificial Intelligence
A new framework called M-Eval has been introduced to improve the reliability of retrieval-augmented generation (RAG) systems in medical question-answering. By addressing issues like incorrect information and hallucinations, this framework aims to enhance the integration of large language models with medical literature. This is significant as it could lead to more accurate and trustworthy responses in medical settings, ultimately benefiting healthcare professionals and patients alike.
— Curated by the World Pulse Now AI Editorial System

