Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

by Facebook AI Research · free · Last verified 2026-03-17

Introduces Retrieval-Augmented Generation (RAG), combining parametric memory (language model weights) with non-parametric memory (dense retrieval over Wikipedia) for knowledge-intensive NLP tasks. RAG models achieve state-of-the-art on open-domain QA benchmarks and produce more specific, factual, and diverse responses than pure parametric models.