Retrieval-Augmented Generation (RAG)

Combines retrieval-based and generative-based approaches to generate responses by retrieving relevant information from a large corpus. RAG is a text generation technique that combines retrieval-based and generative-based approaches. It involves retrieving relevant information from a large corpus of text and then using that information to generate new text. RAG can be used for a variety of tasks, such as question-answering, summarization, and translation.