Protocol for evaluating ChatGPT in biomedical association generation and verification using a RAG-enabled, cross-model majority voting workflow
Researchers have developed a protocol to evaluate ChatGPT's capabilities in generating and verifying biomedical associations. The method employs a Retrieval-Augmented Generation (RAG) approach, leveraging open-source LLMs to cross-validate information and detect hallucinations. This protocol aims to enhance the reliability of LLM-generated biomedical data by using one LLM to verify the content produced by another. AI
IMPACT This protocol could lead to more reliable LLM-generated biomedical data, improving research accuracy.