Martin Schrimpf

3.0k total citations · 1 hit paper
15 papers, 721 citations indexed

About

Martin Schrimpf is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Martin Schrimpf has authored 15 papers receiving a total of 721 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 8 papers in Cognitive Neuroscience and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Martin Schrimpf's work include Neural dynamics and brain function (4 papers), Topic Modeling (4 papers) and Neurobiology of Language and Bilingualism (3 papers). Martin Schrimpf is often cited by papers focused on Neural dynamics and brain function (4 papers), Topic Modeling (4 papers) and Neurobiology of Language and Bilingualism (3 papers). Martin Schrimpf collaborates with scholars based in United States, Switzerland and Sweden. Martin Schrimpf's co-authors include James J. DiCarlo, Evelina Fedorenko, Greta Tuckute, Eghbal A. Hosseini, Carina Kauf, Nancy Kanwisher, Idan Blank, Joshua B. Tenenbaum, Daniel Yamins and Aran Nayebi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and SHILAP Revista de lepidopterología.

In The Last Decade

Martin Schrimpf

15 papers receiving 714 citations

Hit Papers

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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.

The neural architecture of language: Integrative modeling converges on predictive processing

2021 241 citations Martin Schrimpf, Idan Blank et al. Proceedings of the National Academy of Sciences profile →

Peers

Countries citing papers authored by Martin Schrimpf

Since Specialization

Citations

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

Fields of papers citing papers by Martin Schrimpf

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Schrimpf

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

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	The LLM Language Network: A Neuroscientific Approach for Identifying Causally Task-Relevant Units 2025 ·Infoscience (Ecole Polytechnique Fédérale de Lausanne) ·(unknown), Greta Tuckute, Antoine Bosselut, Martin Schrimpf	2
2	Artificial Neural Network Language Models Predict Human Brain Responses to Language Even After a Developmentally Realistic Amount of Training 2024 ·SHILAP Revista de lepidopterología ·Eghbal A. Hosseini, Martin Schrimpf, Yian Zhang, (unknown), Noga Zaslavsky, Evelina Fedorenko	11
3	Driving and suppressing the human language network using large language models 2024 ·Nature Human Behaviour ·Greta Tuckute, (unknown), Shashank Srikant, (unknown), (unknown), Martin Schrimpf, Kendrick Kay, Evelina Fedorenko	30
4	Modeling Visual Impairments with Artificial Neural Networks: a Review 2023 ·Infoscience (Ecole Polytechnique Fédérale de Lausanne) ·(unknown), Monica Gori, Martin Schrimpf, Giulia Cappagli, Federica Morelli, Sabrina Signorini, Boris Katz, Andrei Barbu	1
5	Driving and suppressing the human language network using large language models 2023 ·Greta Tuckute, (unknown), Shashank Srikant, (unknown), (unknown), Martin Schrimpf, Kendrick Kay, Evelina Fedorenko	1
6	Beyond linear regression: mapping models in cognitive neuroscience should align with research goals 2022 ·arXiv (Cornell University) ·Anna A. Ivanova, Martin Schrimpf, Stefano Anzellotti, Noga Zaslavsky, Evelina Fedorenko, Leyla Işık	2
7	Unsupervised neural network models of the ventral visual stream 2021 ·Proceedings of the National Academy of Sciences ·Chengxu Zhuang, Siming Yan, Aran Nayebi, Martin Schrimpf, Michael C. Frank, James J. DiCarlo, Daniel Yamins	169
8	The neural architecture of language: Integrative modeling converges on predictive processing breakdown → 2021 ·Proceedings of the National Academy of Sciences ·Martin Schrimpf, Idan Blank, Greta Tuckute, Carina Kauf, Eghbal A. Hosseini, Nancy Kanwisher, Joshua B. Tenenbaum, Evelina Fedorenko	241
9	Chemogenetic suppression of macaque V4 neurons produces retinotopically specific deficits in downstream IT neural activity patterns and core object recognition behavior 2021 ·Journal of Vision ·Kohitij Kar, Martin Schrimpf, Kailyn Schmidt, James J. DiCarlo	1
10	Frivolous Units: Wider Networks Are Not Really That Wide 2021 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Stephen Casper, Xavier Boix, (unknown), Ling Guo, Martin Schrimpf, Kasper Vinken, Gabriel Kreiman	4
11	Integrative Benchmarking to Advance Neurally Mechanistic Models of Human Intelligence 2020 ·Neuron ·Martin Schrimpf, Jonas Kubilius, (unknown), N. Apurva Ratan Murty, Robert Ajemian, James J. DiCarlo	110
12	Is it that simple? The use of linear models in cognitive neuroscience 2020 ·Anna A. Ivanova, Martin Schrimpf, Leyla Işık, Stefano Anzellotti, Noga Zaslavsky, Evelina Fedorenko	1
13	Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs 2019 ·Lirias (KU Leuven) ·Jonas Kubilius, Martin Schrimpf, Kohitij Kar, Ha Hong, Najib J. Majaj, Rishi Rajalingham, Elias B. Issa, Pouya Bashivan, (unknown), Kailyn Schmidt, Aran Nayebi, Daniel M. Bear, Daniel Yamins, James J. DiCarlo	35
14	Single units in a deep neural network functionally correspond with neurons in the brain: preliminary results 2018 ·DSpace@MIT (Massachusetts Institute of Technology) ·(unknown), (unknown), Martin Schrimpf, Pouya Bashivan, Kohitij Kar, Tomaso Poggio, James J. DiCarlo, Xavier Boix	4
15	Recurrent computations for visual pattern completion 2018 ·Proceedings of the National Academy of Sciences ·Hanlin Tang, Martin Schrimpf, William Lotter, Charlotte Moerman, Ana Paredes, (unknown), (unknown), David Cox, Gabriel Kreiman	109

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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