Retrieval-Augmented Generation (RAG): Architecture, Mechanisms, and Core Advantages
Retrieval-Augmented Generation (RAG) represents a paradigm shift in natural language processing (NLP), integrating large language models (LLMs) with dynamic information retrieval systems to produce responses that are both contextually enriched and factually grounded (Lewis et al. 2020). At its core, the RAG architecture couples a conventional generative model—one that
