Traditional RAG can struggle with highly structured, human-defined knowledge systems.
RAG was introduced by Meta AI in 2020 as a method to improve Large Language Model (LLM) accuracy by grounding responses in retrieved, external data. 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 eccentric_rag_2020_remaster