Analyzing 16,193 LLM Papers for Fun and Profits
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 10 of its 19 references that are in the map. First posted on arXiv 11 Apr 2025.
Builds on
10 of 19 references.
References · 10
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2024The Llama 3 Herd of Modelscited by 14,715
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
- 2022One Embedder, Any Task: Instruction-Finetuned Text Embeddingscited by 333
- 2022OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and conceptscited by 177
- 2023A Bibliometric Review of Large Language Models Research from 2017 to 2023cited by 57
- 2020Examining Citations of Natural Language Processing Literaturecited by 20
- 2023A Diachronic Analysis of Paradigm Shifts in NLP Research: When, How, and Why?cited by 14
- 2017A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovationscited by 13
Built on by
Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2026Real Money, Fake Models: Deceptive Model Claims in Shadow APIscited by 8
- 2025Specification and Detection of LLM Code Smellscited by 0
- 2026Fairness in Multi-Agent Systems for Software Engineering: An SDLC-Oriented Rapid Reviewcited by 0
- 2026LLM Code Smells: A Taxonomy and Detection Approachcited by 0
- 2026LLM Code Smells: A Taxonomy and Detection Approach21 May 2026
- 2026Fairness in Multi-Agent Systems for Software Engineering: An SDLC-Oriented Rapid Review10 Apr 2026
- 2026Real Money, Fake Models: Deceptive Model Claims in Shadow APIs2 Mar 2026
- 2025Specification and Detection of LLM Code Smells19 Dec 2025