Retrieval-Augmented Generation (RAG)

Also known as: RAG

Retrieval-augmented generation grounds a language model's output in external documents fetched at query time. Rather than relying only on parameters learned during training, a RAG system retrieves relevant passages from a knowledge base and places them in the prompt, so answers can cite current, domain-specific information and are less prone to hallucination.