[Summary] Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
TL;DR Generative Large Language Models (LLMs) are limited to generate text based on their training data which means any extension to additional sources necessitates additional training. Retrieval Augmented Generation (RAG) is a method that combines the use of a database with LLMs enables updating the LLM knowledge and make it more precise for specific applications. Method Building blocks The method consists of 3 building blocks. Document index. A pre-trained model was used to encode documents into embeddings to create the index....