Awesome-LLM/paper_list/Retrieval_Augmented_Generation.md

Retrieval-Augmented Generation

Retrieval-Augmented Generation (RAG) combines a retriever model to fetch relevant documents from a corpus and a generator model to produce responses based on both the retrieved documents and the original input, enhancing the generation with external knowledge.

Useful Resource

• Retrieval-Augmented Generation_Paper - The Original Paper on RAG published by Meta in 2020.
• Retrieval-Augmented Geneartion Survey - A Comprehensive and High-quality Survey Conducted by Tongji University and Fudan University on RAG in 2023.