Retrieval-augmented generation Trend

Retrieval-Augmented Generation (RAG) is a technique in natural language processing (NLP) that enhances the accuracy and relevance of responses generated by large language models (LLMs). RAG works by combining the strengths of both retrieval-based models, which extract information from external sources, and generative models, which create original content.