Structural shifts in institutional participation and collaboration within the AI arXiv preprint research ecosystem
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Abstract (arXiv)
The emergence of large language models (LLMs) represents a significant technological shift within the scientific ecosystem, particularly within the field of artificial intelligence (AI). This paper examines structural changes in the AI research landscape using a dataset of arXiv preprints (cs.AI) from 2021 through 2025. Given the rapid pace of AI development, the preprint ecosystem has become a critical barometer for real-time scientific shifts, often preceding formal peer-reviewed publication by months or years. By employing a multi-stage data collection and enrichment pipeline in conjunction with LLM-based institution classification, we analyze the evolution of publication volumes, author team sizes, and academic--industry collaboration patterns. Our results reveal an unprecedented surge in publication output following the introduction of ChatGPT, with academic institutions continuing to provide the largest volume of research. However, we observe that academic--industry collaboration is still suppressed, as measured by a Normalized Collaboration Index (NCI) that remains significantly below the random-mixing baseline across all major subfields. These findings highlight a continuing institutional divide and suggest that the capital-intensive nature of generative AI research may be reshaping the boundaries of scientific collaboration.
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References · 15
- 2024OmniParser for Pure Vision Based GUI Agentcited by 198
- 2023Co-Writing with Opinionated Language Models Affects Users' Viewscited by 148
- 2024Delving into LLM-assisted writing in biomedical publications through excess vocabularycited by 78
- 2020The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Researchcited by 67
- 2023A Bibliometric Review of Large Language Models Research from 2017 to 2023cited by 57
- 2025The Widespread Adoption of Large Language Model-Assisted Writing Across Societycited by 51
- 2023The Elephant in the Room: Analyzing the Presence of Big Tech in Natural Language Processing Researchcited by 27
- 2024The Compute Divide in Machine Learning: A Threat to Academic Contribution and Scrutiny?cited by 20
- 2024Academic collaboration on large language model studies increases overall but varies across disciplinescited by 6
- 2017Popularity of arXiv.org within Computer Sciencecited by 5
- 2025Estimating the prevalence of LLM-assisted text in scholarly writingcited by 4
- 2022Impactful scientists have higher tendency to involve collaborators in new topicscited by 3
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