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A Bibliometric Review of Large Language Models Research from 2017 to 2023

Authors:

Libby HemphillAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology, Volume 15, Issue 5

Article No.: 91, Pages 1 - 25

https://doi.org/10.1145/3664930

Published: 21 October 2024 Publication History

Abstract

Large language models (LLMs), such as OpenAI's Generative Pre-trained Transformer (GPT), are a class of language models that have demonstrated outstanding performance across a range of natural language processing (NLP) tasks. LLMs have become a highly sought-after research area because of their ability to generate human-like language and their potential to revolutionize science and technology. In this study, we conduct bibliometric and discourse analyses of scholarly literature on LLMs. Synthesizing over 5,000 publications, this article serves as a roadmap for researchers, practitioners, and policymakers to navigate the current landscape of LLMs research. We present the research trends from 2017 to early 2023, identifying patterns in research paradigms and collaborations. We start with analyzing the core algorithm developments and NLP tasks that are fundamental in LLMs research. We then investigate the applications of LLMs in various fields and domains, including medicine, engineering, social science, and humanities. Our review also reveals the dynamic, fast-paced evolution of LLMs research. Overall, this article offers valuable insights into the current state, impact, and potential of LLMs research and its applications.

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Cited By

Boutadjine AHarrag FShaalan K(2025)Human vs. Machine: A Comparative Study on the Detection of AI-Generated ContentACM Transactions on Asian and Low-Resource Language Information Processing10.1145/370888924:2(1-26)Online publication date: 10-Feb-2025
https://dl.acm.org/doi/10.1145/3708889
Yan YHou YXiao YZhang RWang Q(2025)KNowNEt:Guided Health Information Seeking from LLMs via Knowledge Graph IntegrationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345636431:1(547-557)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TVCG.2024.3456364
Sasaki YWashizaki HLi JYoshioka NUbayashi NFukazawa Y(2025)Landscape and Taxonomy of Prompt Engineering Patterns in Software EngineeringIT Professional10.1109/MITP.2024.352545827:1(41-49)Online publication date: Jan-2025
https://doi.org/10.1109/MITP.2024.3525458
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Index Terms

A Bibliometric Review of Large Language Models Research from 2017 to 2023
1. Information systems
  1. Information systems applications
    1. Digital libraries and archives
2. Social and professional topics
  1. Professional topics
    1. History of computing

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cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 15, Issue 5

October 2024

719 pages

EISSN:2157-6912

DOI:10.1145/3613688

Editor:
Huan Liu
Arizona State University, AZ

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Publication History

Published: 21 October 2024

Online AM: 13 May 2024

Accepted: 15 April 2024

Revised: 15 April 2024

Received: 10 August 2023

Published in TIST Volume 15, Issue 5

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Cited By

Boutadjine AHarrag FShaalan K(2025)Human vs. Machine: A Comparative Study on the Detection of AI-Generated ContentACM Transactions on Asian and Low-Resource Language Information Processing10.1145/370888924:2(1-26)Online publication date: 10-Feb-2025
https://dl.acm.org/doi/10.1145/3708889
Yan YHou YXiao YZhang RWang Q(2025)KNowNEt:Guided Health Information Seeking from LLMs via Knowledge Graph IntegrationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345636431:1(547-557)Online publication date: 1-Jan-2025
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