Meta (United States)

2.1k papers and 172.3k indexed citations

About

In recent decades, authors affiliated with Meta (United States) have published 2.1k papers, which have received a total of 172.3k indexed citations. Scholars at this organization have produced 552 papers in Artificial Intelligence, 360 papers in Computer Vision and Pattern Recognition and 356 papers in Computer Networks and Communications on the topics of Topic Modeling (140 papers), Cloud Computing and Resource Management (114 papers) and Complex Network Analysis Techniques (92 papers). Their work is cited by papers focused on Computer Vision and Pattern Recognition (55.6k citations), Artificial Intelligence (47.8k citations) and Information Systems (14.3k citations). Authors at Meta (United States) collaborate with scholars in United States, China and Israel and have published in prestigious journals including Nature, Science and Proceedings of the National Academy of Sciences. Some of Meta (United States)'s most productive authors include Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio, Ross Girshick, Kaiming He, Shaoqing Ren, Jian Sun, Cameron Marlow, Ming Yang and Adam Kramer.

In The Last Decade

Meta (United States)

1.9k papers receiving 170.3k citations

Countries citing scholars working at Meta (United States)

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Meta (United States). It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers produced at Meta (United States) with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meta (United States) more than expected).

Fields of papers published by authors at Meta (United States)

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Meta (United States) at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Meta (United States) at the time of their publication.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026