Improving Retrieval Augmented Generation with CRAG

Retrieval Augmented Generation (RAG) is a technique that integrates external knowledge sources into large language models (LLMs) to enhance their response generation capabilities. However, one limitation of vanilla RAG systems is that if the initial retrieval of documents is not accurate or relevant, the final response can suffer.

To address this, researchers have proposed a novel method called Corrective Retrieval Augmented Generation (CRAG). The core idea behind CRAG is to introduce a separate “evaluator” component to assess the quality and…