Analyzing 16,193 LLM Papers for Fun and Profits

• URL: http://arxiv.org/abs/2504.08619v4
• Date: Tue, 22 Apr 2025 19:13:09 GMT
• Title: Analyzing 16,193 LLM Papers for Fun and Profits
• Authors: Zhiqiu Xia, Lang Zhu, Bingzhe Li, Feng Chen, Qiannan Li, Chunhua Liao, Feiyi Wang, Hang Liu,
• Abstract summary: Large Language Models (LLMs) are reshaping the landscape of computer science research.<n>This study provides a comprehensive analysis of the publication trend of LLM-related papers in 77 top-tier computer science conferences over the past six years.
• Score: 6.295399100138773
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models (LLMs) are reshaping the landscape of computer science research, driving significant shifts in research priorities across diverse conferences and fields. This study provides a comprehensive analysis of the publication trend of LLM-related papers in 77 top-tier computer science conferences over the past six years (2019-2024). We approach this analysis from four distinct perspectives: (1) We investigate how LLM research is driving topic shifts within major conferences. (2) We adopt a topic modeling approach to identify various areas of LLM-related topic growth and reveal the topics of concern at different conferences. (3) We explore distinct contribution patterns of academic and industrial institutions. (4) We study the influence of national origins on LLM development trajectories. Synthesizing the findings from these diverse analytical angles, we derive ten key insights that illuminate the dynamics and evolution of the LLM research ecosystem.

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