Retrieval-Augmented Generation

A technique that enhances language model outputs by first retrieving relevant documents or data from an external knowledge base, then providing that information as context for the model to generate a grounded response. RAG reduces hallucination and allows models to answer questions about information that was not in their training data or may have changed since training.