Retrieval-Augmented Generation (RAG)

RAG grounds a model's output in retrieved documents to reduce hallucination and add fresh knowledge. It is not a cure-all: retrieval quality bounds answer quality, models can ignore or misread retrieved context, and long contexts suffer recall degradation (see the linked findings). Treat retrieval as a noisy oracle, not ground truth.