mlsanityData to 14 Oct 2026

The Role of Computing Resources in Publishing Foundation Model Research

arXiv 2510.13621 ↗First posted 15 Oct 2025cs.CY cs.AIcited by 2

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Abstract (arXiv)

Cutting-edge research in Artificial Intelligence (AI) requires considerable resources, including Graphics Processing Units (GPUs), data, and human resources. In this paper, we evaluate of the relationship between these resources and the scientific advancement of foundation models (FM). We reviewed 6517 FM papers published between 2022 to 2024, and surveyed 229 first-authors to the impact of computing resources on scientific output. We find that increased computing is correlated with national funding allocations and citations, but our findings don't observe the strong correlations with research environment (academic or industrial), domain, or study methodology. We advise that individuals and institutions focus on creating shared and affordable computing opportunities to lower the entry barrier for under-resourced researchers. These steps can help expand participation in FM research, foster diversity of ideas and contributors, and sustain innovation and progress in AI. The data will be available at: https://mit-calc.csail.mit.edu/

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 14 of its 35 references that are in the map. First posted on arXiv 15 Oct 2025.

Builds on

14 of 35 references.

References · 14

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2023A Survey of Large Language Modelscited by 2,576
  3. 2023Foundation Models in Robotics: Applications, Challenges, and the Futurecited by 216
  4. 2019Show Your Work: Improved Reporting of Experimental Resultscited by 169
  5. 2024The rising costs of training frontier AI modelscited by 95
  6. 2024On the Societal Impact of Open Foundation Modelscited by 65
  7. 2023A Bibliometric Review of Large Language Models Research from 2017 to 2023cited by 57
  8. 2020Examining Citations of Natural Language Processing Literaturecited by 20
  9. 2024Foundation Model Transparency Reportscited by 14
  10. 2021What Have We Learned from OpenReview?cited by 7
  11. 2024Neural Scaling Laws in Roboticscited by 7
  12. 2024100K or 100 Days: Trade-offs when Pre-Training with Academic Resourcescited by 6
2 more
  1. 2023Who is leading in AI? An analysis of industry AI researchcited by 4
  2. 2019A Retrospective Recount of Computer Architecture Research with a Data-Driven Study of Over Four Decades of ISCA Publicationscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Science Is Falling Behind the Frontier: Foundation Model Adoption Across Half a Million Paperscited by 5
  2. 2026Accelerating Scientific Research with Gemini in the Real-Worldcited by 2