Mitchell Wortsman

2.8k total citations · 2 hit papers
9 papers, 513 citations indexed

About

Mitchell Wortsman is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Surgery. According to data from OpenAlex, Mitchell Wortsman has authored 9 papers receiving a total of 513 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Surgery. Recurrent topics in Mitchell Wortsman's work include Domain Adaptation and Few-Shot Learning (5 papers), Advanced Neural Network Applications (4 papers) and Multimodal Machine Learning Applications (2 papers). Mitchell Wortsman is often cited by papers focused on Domain Adaptation and Few-Shot Learning (5 papers), Advanced Neural Network Applications (4 papers) and Multimodal Machine Learning Applications (2 papers). Mitchell Wortsman collaborates with scholars based in United States, Germany and United Kingdom. Mitchell Wortsman's co-authors include Gabriel Ilharco, Ludwig Schmidt, Romain Beaumont, Ross Wightman, Jenia Jitsev, Mehdi Cherti, Christoph Schuhmann, Ali Farhadi, Hannaneh Hajishirzi and Ludwig Schmidt and has published in prestigious journals such as npj Digital Medicine, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

In The Last Decade

Mitchell Wortsman

9 papers receiving 486 citations

Hit Papers

Reproducible Scaling Laws for Contrastive Language-Image ... 2022 2026 2023 2024 2023 2022 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Reproducible Scaling Laws for Contrastive Language-Image Learning
    2023 213 citations Mehdi Cherti, Romain Beaumont et al. profile →
  2. Robust fine-tuning of zero-shot models
    2022 208 citations Mitchell Wortsman, Gabriel Ilharco et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mitchell Wortsman United States 6 328 286 28 23 21 9 513
Gabriel Ilharco United States 7 354 1.1× 318 1.1× 31 1.1× 25 1.1× 22 1.0× 12 553
Roberto Olmos Spain 5 287 0.9× 269 0.9× 25 0.9× 22 1.0× 8 0.4× 5 450
Hangbo Bao China 5 231 0.7× 279 1.0× 13 0.5× 18 0.8× 10 0.5× 8 432
Saurav Kadavath United States 2 346 1.1× 429 1.5× 16 0.6× 48 2.1× 16 0.8× 2 580
Guangyao Chen China 5 138 0.4× 238 0.8× 26 0.9× 25 1.1× 26 1.2× 11 391
Norman Mu United States 3 361 1.1× 407 1.4× 16 0.6× 48 2.1× 16 0.8× 6 570
Chaoyou Fu China 10 350 1.1× 129 0.5× 32 1.1× 14 0.6× 12 0.6× 25 536
Chuming Li China 9 187 0.6× 145 0.5× 27 1.0× 10 0.4× 20 1.0× 18 326
Mostafa El Mallahi Morocco 14 232 0.7× 107 0.4× 21 0.8× 28 1.2× 34 1.6× 44 391
Santosh Divvala United States 9 664 2.0× 333 1.2× 54 1.9× 13 0.6× 13 0.6× 13 769

Countries citing papers authored by Mitchell Wortsman

Since Specialization
Citations

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

Fields of papers citing papers by Mitchell Wortsman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mitchell Wortsman. 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 Mitchell Wortsman. The network helps show where Mitchell Wortsman may publish in the future.

Co-authorship network of co-authors of Mitchell Wortsman

This figure shows the co-authorship network connecting the top 25 collaborators of Mitchell Wortsman. A scholar is included among the top collaborators of Mitchell Wortsman 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 Mitchell Wortsman. Mitchell Wortsman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Chan, Justin, Mitchell Wortsman, Achal Dave, et al.. (2024). Detecting clinical medication errors with AI enabled wearable cameras. npj Digital Medicine. 7(1). 287–287. 3 indexed citations
2.
Gadre, Samir Yitzhak, Mitchell Wortsman, Gabriel Ilharco, Ludwig Schmidt, & Shuran Song. (2023). CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation. 23171–23181. 66 indexed citations
3.
Cherti, Mehdi, Romain Beaumont, Ross Wightman, et al.. (2023). Reproducible Scaling Laws for Contrastive Language-Image Learning. 2818–2829. 213 indexed citations breakdown →
4.
Wortsman, Mitchell, et al.. (2022). Exploring The Landscape of Distributional Robustness for Question Answering Models. 5971–5987. 6 indexed citations
5.
Beaumont, Romain, et al.. (2022). LAION-5B: An Open Large-Scale Dataset for Training Next Generation Image-Text Models. 25278–25294. 1 indexed citations
6.
Wortsman, Mitchell, Gabriel Ilharco, Jong Wook Kim, et al.. (2022). Robust fine-tuning of zero-shot models. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 7949–7961. 208 indexed citations breakdown →
7.
Wortsman, Mitchell, et al.. (2021). Learning Neural Network Subspaces. International Conference on Machine Learning. 11217–11227. 6 indexed citations
8.
Kusupati, Aditya, et al.. (2020). Soft Threshold Weight Reparameterization for Learnable Sparsity. International Conference on Machine Learning. 1. 5544–5555. 3 indexed citations
9.
Wortsman, Mitchell, Ali Farhadi, & Mohammad Rastegari. (2019). Discovering Neural Wirings. arXiv (Cornell University). 32. 2680–2690. 7 indexed citations

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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