Roger Levy

Roger Levy is an associate professor in MIT’s Department of Brain and Cognitive Sciences. His research focuses on theoretical and applied questions in the processing and acquisition of natural language. Linguistic communication involves the resolution of uncertainty over a potentially unbounded set of possible signals and meanings. How can a fixed set of knowledge and resources be deployed to manage this uncertainty? And how is this knowledge acquired? To address these questions he combines computational modeling, psycholinguistic experimentation, and analysis of large naturalistic language datasets. This work furthers our understanding of the cognitive underpinning of language processing and acquisition, and helps us design models and algorithms that will allow machines to process human language.

Before coming to MIT, Levy was a professor at the University of California at San Diego. He was a Fulbright Fellow at the Inter-University Program for Chinese Language Study in Taipei, a research student at the University of Tokyo, and a postdoc at the University of Edinburgh. His awards include a Sloan Research Fellowship, an NSF Career Award, and a fellowship at Stanford’s Center for Advanced Study in the Behavioral Sciences. Levy earned a BS in mathematics at the University of Arizona, and a PhD at Stanford University.

Selected Publications

• Wang, Y. et al. (2021). Controlled Evaluation of Grammatical Knowledge in Mandarin Chinese Language Models. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5604–5620
• Wilcox, E., Vani, P., and Levy, R. (2021). A Targeted Assessment of Incremental Processing in Neural LanguageModels and Humans. ACL.
• Mao, J., Shi, H., Wu, J., Levy, R., and Tenenbaum, J. (2021). Grammar-Based Grounded Lexicon Learning. Conference and Workshop on Neural Information Processing Systems (NeurIPS).

Media

• Jan. 24, 2020. New York Times, “She’s the Next President. Wait, Did You Read That Right?” on the Psychological Science study: Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections.
• May 29, 2019. MIT News, “Teaching Language Models Grammar Really Does Make Them Smarter” on the NAACL study: Neural Language Models as Psycholinguistic Subjects.
• May 22, 2018. MIT News, “Gauging Language Proficiency through Eye Movement” on the NAACL study: Assessing Language Proficiency from Eye Movements in Reading.
• April 6, 2017: MIT News, “Articles of Faith” on the Psychological Science study: The Emergence of an Abstract Grammatical Category in Children’s Early Speech.

Videos