分析1.6万篇大模型论文，揭示研究趋势与机构差异
Analyzing 16,193 LLM Papers for Fun and Profits
- 从四个视角分析6年大模型论文发表趋势
- 发现学术与工业界研究重点明显不同
- 揭示国家背景对大模型发展路径的影响
大语言模型（LLMs）正在重塑计算机科学领域的研究格局，推动各大会议和学科的研究重点发生显著变化。本研究全面分析了2019至2024年共77个顶级计算机科学会议中16,193篇大模型相关论文的发表趋势。从四个角度展开：(1) 探讨大模型研究如何引发主要会议的主题转变；(2) 采用主题建模方法识别大模型相关话题的增长领域，并揭示不同会议的关注重点；(3) 分析学术机构与产业机构的贡献模式差异；(4) 研究国家起源对大模型发展路径的影响。综合多维度分析，提炼出十项关键洞察，深入揭示大模型研究生态系统的动态演化过程。
原文摘要 · Abstract (English)
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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