RAG allows models to leverage up-to-date, domain-specific, or private knowledge without retraining, making it highly suitable for fast-changing data environments.
The field has moved beyond basic RAG, diversifying into hybrid retrievers, iterative retrieval loops, and graph-based retrieval systems. eccentric_rag_2020_remaster
Recent developments emphasize modular pipelines and better evaluation protocols, moving away from simple "retrieve-and-generate" approaches. 2. Core Advantages of Modern RAG RAG allows models to leverage up-to-date