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Large language models (LLMs) are a class of language models that havedemonstrated outstanding performance across a range of natural languageprocessing (NLP) tasks and have become a highly sought-after research area,because of their ability to generate human-like language and their potential torevolutionize science and technology. In this study, we conduct bibliometricand discourse analyses of scholarly literature on LLMs. Synthesizing over 5,000publications, this paper serves as a roadmap for researchers, practitioners,and policymakers to navigate the current landscape of LLMs research. We presentthe research trends from 2017 to early 2023, identifying patterns in researchparadigms and collaborations. We start with analyzing the core algorithmdevelopments and NLP tasks that are fundamental in LLMs research. We theninvestigate the applications of LLMs in various fields and domains includingmedicine, engineering, social science, and humanities. Our review also revealsthe dynamic, fast-paced evolution of LLMs research. Overall, this paper offersvaluable insights into the current state, impact, and potential of LLMsresearch and its applications.

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