Mayo Clinic Solves LLM Hallucination Problem with Reverse RAG
2025-03-15
Large language models (LLMs) suffer from 'hallucinations' – generating inaccurate information – a particularly dangerous issue in healthcare. Mayo Clinic tackled this with a novel 'reverse RAG' technique. By linking extracted information to its original source, this method eliminated almost all data-retrieval-based hallucinations, enabling the model's deployment across its clinical practice. The technique combines the CURE algorithm and vector databases, ensuring traceability of every data point to its origin. This enhances model reliability and trustworthiness, significantly reducing physician workload and opening new avenues for personalized medicine.
AI
Reverse RAG