Query Optimization For Parametric Knowledge Refinement In Retrieval-augmented Large Language Models

Abstract

We introduce the \textit\{Extract-Refine-Retrieve-Read\} (ERRR) framework, a novel approach designed to bridge the pre-retrieval information gap in Retrieval-Augmented Generation (RAG) systems through query optimization tailored to meet the specific knowledge requirements of Large Language Models (LLMs). Unlike conventional query optimization techniques used in RAG, the ERRR framework begins by ex