Analyzing 16,193 LLM Papers for Fun and Profits
This work provides a comprehensive overview of LLM research trends, which is useful for researchers and policymakers tracking the field's evolution, though it is incremental as it applies existing analysis methods to new data.
The study analyzed 16,193 LLM papers from 77 top-tier computer science conferences from 2019 to 2024 to understand publication trends and their impact on research priorities, deriving ten key insights on topic shifts, institutional contributions, and national influences.
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.