Meta (United States)
Papers in the tracked journals with an author at Meta (United States): per year and category, where they are published, the institutions its researchers write with, and its most-cited papers. A paper counts as corporate when at least one of its authors is affiliated with an institution that OpenAlex classifies as a company; it counts once for each company among its authors' affiliations. Universities are the institutions OpenAlex classifies as education. Also as Markdown.
Key findings#
- From 2017 to 2026 (so far), authors at Meta (United States) took part in 185 papers in the tracked journals, most of them in AI (150), economics (11) and operations research (11).
- It ranks #9 among the companies publishing in the tracked journals from 2023 to 2025.
- 19 of them were published in 2025, against 9 in 2017.
- Since 2023, the institutions with the most of these papers were Georgia Institute of Technology (6), Massachusetts Institute of Technology (6) and University of Electronic Science and Technology of China (6).
- The journals publishing most of them were IEEE Transactions on Pattern Analysis and Machine Intelligence (25), Nature Machine Intelligence (8) and Neural Networks (6).
- The most-cited of them is “Focal Loss for Dense Object Detection” (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018), with 9,547 citations.
Papers per year#
20172026 (so far)
| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---|---|---|---|---|---|---|---|---|---|
| AI | 5 | 11 | 17 | 15 | 19 | 14 | 29 | 20 | 12 | 8 |
| Economics | 1 | 0 | 0 | 1 | 1 | 2 | 1 | 1 | 3 | 1 |
| Operations Research | 1 | 1 | 0 | 0 | 3 | 1 | 2 | 1 | 2 | 0 |
| Statistics | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 |
| Information Systems | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| Marketing | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 |
| Tourism and Hospitality | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
| Higher Education and Research | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
| Accounting | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Management | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| All categories | 9 | 12 | 17 | 20 | 25 | 17 | 33 | 23 | 19 | 10 |
Where the papers come from#
| # | Journal | Papers |
|---|---|---|
| 1 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 25 |
| 2 | Nature Machine Intelligence | 8 |
| 3 | Neural Networks | 6 |
| 4 | Machine Learning | 5 |
| 5 | International Journal of Computer Vision | 5 |
| 6 | IEEE Transactions on Neural Networks and Learning Systems | 5 |
| 7 | Pattern Recognition | 3 |
| 8 | IEEE Transactions on Knowledge and Data Engineering | 3 |
| 9 | International Journal of Forecasting | 2 |
| 10 | Journal of Econometrics | 2 |
| # | Institution | Papers |
|---|---|---|
| 1 | Georgia Institute of Technology | 6 |
| 2 | Massachusetts Institute of Technology | 6 |
| 3 | University of Electronic Science and Technology of China | 6 |
| 4 | University of Maryland, College Park | 6 |
| 5 | Fudan University | 5 |
| 6 | Harbin Institute of Technology | 5 |
| 7 | Stanford University | 5 |
| 8 | Adobe Systems (United States) | 4 |
| 9 | Carnegie Mellon University | 4 |
| # | Country | Papers |
|---|---|---|
| 1 | United States | 85 |
| 2 | China | 33 |
| 3 | United Kingdom | 5 |
| 4 | India | 5 |
| 5 | Australia | 4 |
| 6 | Canada | 4 |
| 7 | Germany | 4 |
| 8 | Italy | 4 |
| 9 | Singapore | 4 |
| 10 | Switzerland | 3 |
| # | Keyword | Papers |
|---|---|---|
| 1 | large language models | 7 |
| 2 | adversarial robustness | 3 |
| 3 | adversarial training | 3 |
| 4 | catastrophic forgetting | 3 |
| 5 | egocentric video | 3 |
| 6 | recommender systems | 3 |
| 7 | Nesterov acceleration | 2 |
| 8 | Segment Anything Model | 2 |
| 9 | benchmark challenge | 2 |
| 10 | biometric datasets | 2 |
Most-cited papers#
Cite this page
Scholar4AI. (2026). Meta (United States). Journal Research Rankings. Retrieved October 31, 2026, from https://scholar4ai.com/companies/meta-united-states
@misc{scholar4ai-companies-meta-united-states,
author = {{Scholar4AI}},
title = {Meta (United States)},
year = {2026},
howpublished = {\url{https://scholar4ai.com/companies/meta-united-states}},
urldate = {2026-10-31},
note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}