MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation

This research paper describes a new computer program called MAIN-RAG that helps large language models (LLMs) like ChatGPT give better answers to questions. LLMs can sometimes give wrong or outdated answers because they are trained on information that can become old. MAIN-RAG tries to fix this by finding documents related to the question and filtering out unhelpful or noisy ones. It uses three AI agents to do this. The first agent tries to answer the question based on each document. The second agent judges if the document is helpful by comparing the AI’s answer to the actual answer. The third agent then uses the filtered documents to give a final, hopefully better, answer. MAIN-RAG is special because it doesn’t need extra training and can adapt to different types of questions. Experiments showed that MAIN-RAG improved the accuracy of answers compared to other methods, especially when the questions needed up-to-date information.