Neal Gregory Lawton

A Comparison of Independent and Joint Fine-tuning Strategies for Retrieval-Augmented Generation

Retrieval augmented generation (RAG) is a popular framework for question answering that is powered by two large language models (LLMs): an embedding model that retrieves context documents from a database that are relevant to a given question, and a generator model that uses the retrieved context to