Retrieval-Augmented Generation

Retrieval-Augmented Generation (RAG) retrieves relevant external knowledge before passing it into a generative language model to produce grounded responses. It mitigates factual hallucinations stemming from static parametric memory, enables fast knowledge updates, and provides verifiable citation sources.