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August 7, 2024 by Gary Price

Research Article (Preprint): “Wiping Out the Limitations of Large Language Models — A Taxonomy for Retrieval Augmented Generation”

August 7, 2024 by Gary Price

The article (preprint) linked below was recently shared on arXiv.

Title

Wiping Out the Limitations of Large Language Models — A Taxonomy for Retrieval Augmented Generation

Authors

Mahei Manhai Li
University of Kassel

Irina Nikishina
University of Hamburg

Özge Sevgili
University of Kassel
University of Hamburg

Martin Semman
University of Hamburg

Source

via arXiv

Abstract

Current research on RAGs is distributed across various disciplines, and since the technology is evolving very quickly, its unit of analysis is mostly on technological innovations, rather than applications in business contexts. Thus, in this research, we aim to create a taxonomy to conceptualize a comprehensive overview of the constituting characteristics that define RAG applications, facilitating the adoption of this technology in the IS community. To the best of our knowledge, no RAG application taxonomies have been developed so far. We describe our methodology for developing the taxonomy, which includes the criteria for selecting papers, an explanation of our rationale for employing a Large Language Model (LLM)-supported approach to extract and identify initial characteristics, and a concise overview of our systematic process for conceptualizing the taxonomy. Our systematic taxonomy development process includes 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 Retrieval-Augmented Generation (RAG) applications. When discussing our findings, we also detail the specific research areas and pose key research questions to guide future information system researchers as they explore the emerging topics of RAG systems.

Table 1: RAG Taxonomy created from twenty-eight papers within four iterations Source: arXiv:2408.02854

Direct to Abstract, Link to Full Text

Filed under: Journal Articles, News

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About Gary Price

Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com.

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