12 Types of Retrieval-Augmented Generation (RAG)

Retrieval-Augmented Generation (RAG) is a very popular technique used in LLMs to improve the accuracy and relevance of their responses. Instead of relying solely on the information stored within the model, RAG retrieves relevant external documents or data during the response generation process. This leads to more accurate and contextually appropriate answers, especially for tasks needing specific or up-to-date knowledge.

Here is a list of 12 types of RAG that can be used for different purposes: