Roger Lévy

22.9k total citations · 6 hit papers
146 papers, 13.5k citations indexed

About

Roger Lévy is a scholar working on Artificial Intelligence, Developmental and Educational Psychology and Cognitive Neuroscience. According to data from OpenAlex, Roger Lévy has authored 146 papers receiving a total of 13.5k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Artificial Intelligence, 54 papers in Developmental and Educational Psychology and 53 papers in Cognitive Neuroscience. Recurrent topics in Roger Lévy's work include Natural Language Processing Techniques (58 papers), Neurobiology of Language and Bilingualism (49 papers) and Topic Modeling (46 papers). Roger Lévy is often cited by papers focused on Natural Language Processing Techniques (58 papers), Neurobiology of Language and Bilingualism (49 papers) and Topic Modeling (46 papers). Roger Lévy collaborates with scholars based in United States, United Kingdom and Germany. Roger Lévy's co-authors include Harry Tily, Dale J. Barr, Christoph Scheepers, Nathaniel J. Smith, Gabriel Doyle, Nuno Vasconcelos, Gert Lanckriet, José Costa Pereira, Nikhil Rasiwasia and Emanuele Coviello and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Roger Lévy

134 papers receiving 12.9k citations

Hit Papers

Random effects structure ... 2007 2026 2013 2019 2013 2007 2010 2013 2013 2.0k 4.0k 6.0k

Author Peers

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

Author Last Decade Papers Cites
Roger Lévy 6.4k 4.5k 3.9k 3.5k 2.0k 146 13.5k
Christoph Scheepers 6.2k 1.0× 4.1k 0.9× 1.4k 0.4× 4.1k 1.2× 1.5k 0.7× 87 11.0k
Ray Jackendoff 5.6k 0.9× 3.5k 0.8× 4.5k 1.2× 6.5k 1.8× 8.3k 4.0× 143 18.1k
Emmanuel Dupoux 4.1k 0.6× 4.0k 0.9× 2.5k 0.6× 3.8k 1.1× 778 0.4× 208 9.8k
Marc Brysbaert 13.9k 2.2× 11.9k 2.7× 5.0k 1.3× 6.8k 1.9× 2.0k 1.0× 267 23.5k
Richard Ν. Aslin 10.4k 1.6× 12.9k 2.9× 3.2k 0.8× 7.8k 2.2× 1.0k 0.5× 242 22.4k
Dale J. Barr 5.3k 0.8× 4.2k 0.9× 1.7k 0.4× 4.2k 1.2× 1.8k 0.9× 37 10.7k
Linda B. Smith 6.5k 1.0× 13.4k 3.0× 2.8k 0.7× 4.8k 1.4× 832 0.4× 328 21.0k
Dominic W. Massaro 5.6k 0.9× 3.2k 0.7× 1.7k 0.4× 5.4k 1.5× 465 0.2× 255 11.3k
Simon Garrod 3.8k 0.6× 2.8k 0.6× 2.6k 0.7× 3.8k 1.1× 2.3k 1.1× 87 9.4k
Robert M. Nosofsky 5.6k 0.9× 6.0k 1.3× 3.5k 0.9× 3.5k 1.0× 291 0.1× 141 12.2k

Countries citing papers authored by Roger Lévy

Since Specialization
Citations

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

Fields of papers citing papers by Roger Lévy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roger Lévy

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

All Works

20 of 20 papers shown
2.
Kauf, Carina, Greta Tuckute, Roger Lévy, Jacob Andreas, & Evelina Fedorenko. (2023). Lexical-Semantic Content, Not Syntactic Structure, Is the Main Contributor to ANN-Brain Similarity of fMRI Responses in the Language Network. SHILAP Revista de lepidopterología. 5(1). 7–42. 10 indexed citations
3.
Wehbe, Leila, Idan Blank, Cory Shain, et al.. (2021). Incremental Language Comprehension Difficulty Predicts Activity in the Language Network but Not the Multiple Demand Network. Cerebral Cortex. 31(9). 4006–4023. 39 indexed citations
4.
Malsburg, Titus von der, et al.. (2020). Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections. Psychological Science. 31(2). 115–128. 18 indexed citations
5.
Wilcox, Ethan, Jon Gauthier, Jennifer Hu, Peng Qian, & Roger Lévy. (2020). On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior.. Cognitive Science. 1 indexed citations
6.
Hu, Jennifer, Jon Gauthier, Peng Qian, Ethan Wilcox, & Roger Lévy. (2020). A Systematic Assessment of Syntactic Generalization in Neural Language Models. DSpace@MIT (Massachusetts Institute of Technology). 18 indexed citations
7.
Wilcox, Ethan, Roger Lévy, & Richard Futrell. (2019). What Syntactic Structures block Dependencies in RNN Language Models. eScholarship (California Digital Library). 1199–1205. 5 indexed citations
8.
Meylan, Stephan C., Michael C. Frank, Brandon Roy, & Roger Lévy. (2017). The Emergence of an Abstract Grammatical Category in Children’s Early Speech. Psychological Science. 28(2). 181–192. 22 indexed citations
9.
Gibson, Edward, Julian Jara‐Ettinger, Roger Lévy, & Steven T. Piantadosi. (2017). The Use of a Computer Display Exaggerates the Connection Between Education and Approximate Number Ability in Remote Populations. Open Mind. 2(1). 37–46. 5 indexed citations
10.
Doyle, Gabriel & Roger Lévy. (2016). Data-driven learning of symbolic constraints for a log-linear model in a phonological setting.. International Conference on Computational Linguistics. 2217–2226. 2 indexed citations
11.
Lévy, Roger, et al.. (2016). Structure-sensitive Noise Inference: Comprehenders Expect Exchange Errors.. Cognitive Science. 13 indexed citations
12.
Fossum, Victoria & Roger Lévy. (2012). Sequential vs. Hierarchical Syntactic Models of Human Incremental Sentence Processing. North American Chapter of the Association for Computational Linguistics. 61–69. 44 indexed citations
13.
Bicknell, Klinton & Roger Lévy. (2012). Why long words take longer to read: the role of uncertainty about word length. North American Chapter of the Association for Computational Linguistics. 21–30. 3 indexed citations
14.
Bicknell, Klinton & Roger Lévy. (2012). Word predictability and frequency effects in a rational model of reading. Cognitive Science. 34(34). 126–131. 9 indexed citations
15.
Park, Youngjun, et al.. (2011). Bilingual Random Walk Models for Automated Grammar Correction of ESL Author-Produced Text. 170–179. 6 indexed citations
16.
Lévy, Roger, et al.. (2011). Automated Whole Sentence Grammar Correction Using a Noisy Channel Model. Meeting of the Association for Computational Linguistics. 934–944. 39 indexed citations
17.
Smith, Nathaniel J. & Roger Lévy. (2010). Fixation durations in first-pass reading reflect uncertainty about word identity. eScholarship (California Digital Library). 32(32). 3 indexed citations
18.
Lévy, Roger, Florencia Reali, & Thomas L. Griffiths. (2008). Modeling the effects of memory on human online sentence processing with particle filters. Neural Information Processing Systems. 21. 937–944. 58 indexed citations
19.
Smith, Nathaniel J. & Roger Lévy. (2008). Probabilistic Prediction and the Continuity of Language Comprehension. SSRN Electronic Journal. 1 indexed citations
20.
Lévy, Roger. (1964). Jacques Gernet. La Chine ancienne, des origines à l'Empire. Périodiques Scientifiques en Édition Électronique.

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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