Gabriel Ilharco

46 total papers · 2.5k total citations
12 papers, 520 citations indexed

About

Gabriel Ilharco is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Gabriel Ilharco has authored 12 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 1 paper in Information Systems. Recurrent topics in Gabriel Ilharco's work include Multimodal Machine Learning Applications (9 papers), Domain Adaptation and Few-Shot Learning (7 papers) and Topic Modeling (7 papers). Gabriel Ilharco is often cited by papers focused on Multimodal Machine Learning Applications (9 papers), Domain Adaptation and Few-Shot Learning (7 papers) and Topic Modeling (7 papers). Gabriel Ilharco collaborates with scholars based in United States, United Kingdom and Austria. Gabriel Ilharco's co-authors include Mitchell Wortsman, Ludwig Schmidt, Ludwig Schmidt, Ross Wightman, Romain Beaumont, Mehdi Cherti, Jenia Jitsev, Christoph Schuhmann, Hannaneh Hajishirzi and Ali Farhadi and has published in prestigious journals such as 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

In The Last Decade

Gabriel Ilharco

12 papers receiving 496 citations

Hit Papers

Reproducible Scaling Laws... 2022 2026 2023 2024 2023 2022 50 100 150

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Gabriel Ilharco 338 303 30 25 23 12 520
Mitchell Wortsman 312 0.9× 273 0.9× 27 0.9× 23 0.9× 18 0.8× 8 481
Yiyu Qiu 250 0.7× 256 0.8× 33 1.1× 17 0.7× 18 0.8× 6 475
K J Joseph 374 1.1× 294 1.0× 37 1.2× 33 1.3× 9 0.4× 12 528
Shuo Yang 218 0.6× 180 0.6× 48 1.6× 22 0.9× 32 1.4× 19 456
Pengguang Chen 245 0.7× 242 0.8× 30 1.0× 15 0.6× 9 0.4× 10 481
Feng Wang 242 0.7× 245 0.8× 32 1.1× 25 1.0× 53 2.3× 15 504
Sheng Jin 310 0.9× 226 0.7× 40 1.3× 37 1.5× 12 0.5× 16 545
Zheda Mai 266 0.8× 416 1.4× 13 0.4× 52 2.1× 33 1.4× 14 534
Guile Wu 338 1.0× 180 0.6× 21 0.7× 16 0.6× 9 0.4× 21 452
Dylan Anderson 294 0.9× 264 0.9× 31 1.0× 19 0.8× 40 1.7× 10 553

Countries citing papers authored by Gabriel Ilharco

Since Specialization
Citations

This map shows the geographic impact of Gabriel Ilharco's research. 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 Gabriel Ilharco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Ilharco more than expected).

Fields of papers citing papers by Gabriel Ilharco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gabriel Ilharco. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gabriel Ilharco. The network helps show where Gabriel Ilharco may publish in the future.

Co-authorship network of co-authors of Gabriel Ilharco

This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Ilharco. A scholar is included among the top collaborators of Gabriel Ilharco based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gabriel Ilharco. Gabriel Ilharco is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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