Creating a Taxonomy for Retrieval Augmented Generation Applications

TL;DR

This paper presents a novel taxonomy for retrieval augmented generation (RAG) applications, providing a structured overview to facilitate understanding and development across various domains.

Contribution

It introduces the first comprehensive RAG application taxonomy with five meta-dimensions and sixteen dimensions, employing a unique iterative method.

Findings

Developed a detailed taxonomy for RAG applications

Identified core dimensions defining RAG characteristics

Facilitated understanding and design of RAG systems

Abstract

In this research, we develop a taxonomy to conceptualize a comprehensive overview of the constituting characteristics that define retrieval augmented generation (RAG) applications, facilitating the adoption of this technology for different application domains. To the best of our knowledge, no holistic RAG application taxonomies have been developed so far. We employ the method foreign to ACL and thus contribute to the set of methods in the taxonomy creation. It comprises four iterative phases designed to refine and enhance our understanding and presentation of RAG's core dimensions. We have developed a total of five meta-dimensions and sixteen dimensions to comprehensively capture the concept of RAG applications. Thus, the taxonomy can be used to better understand RAG applications and to derive design knowledge for future solutions in specific application domains.