thomashikaru

Interests

I study the principles underlying human language and cognition, using NLP, information theory, and probabilistic inference. Click a tile to learn more.

Curriculum Vitae

Thomas Hikaru Clark CV

Publications and Presentations

Publications

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Thomas Hikaru Clark, Carlos Arriaga, Javier Conde, Gonzalo Martínez, & Pedro Reviriego (2026). To Words and Beyond: Probing Large Language Models for Sentence-Level Psycholinguistic Norms of Memorability and Reading Times. arXiv preprint arXiv:2603.12105.
Thomas Hikaru Clark, Greta Tuckute, Bryan Medina, & Evelina Fedorenko (2026). A distinctive meaning makes a sentence memorable. Journal of Memory and Language.
Richard Hudson, Nikolas Gisborne, Thomas Hikaru Clark, Eva Duran Eppler, Willem Hollmann, Andrew Rosta, & Graeme Trousdale (2025). The syntactic constraint on English auxiliary contraction. Journal of Linguistics.
Thomas Hikaru Clark, Moshe Poliak, Tamar Regev, AJ Haskins, Caroline Robertson, & Edward Gibson (2025). The Relationship Between Surprisal and Prosodic Prominence in Conversation Reflects Intelligibility‐Oriented Pressures. Cognitive Science.
Thomas Hikaru Clark, Jacob Hoover Vigly, Edward Gibson, & Roger Levy (2025). Resource-Rational Noisy-Channel Language Processing: Testing the Effect of Algorithmic Constraints on Inferences. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing.
Anna A Ivanova, Aalok Sathe, Benjamin Lipkin, Unnathi U Kumar, Setayesh Radkani, Thomas H Clark, Carina Kauf, Jennifer Hu, RT Pramod, Gabriel Grand, Vivian C Paulun, Maria Ryskina, Ekin Akyürek, Ethan G Wilcox, Nafisa Rashid, Leshem Choshen, Roger Levy, Evelina Fedorenko, Joshua Tenenbaum, & Jacob Andreas (2025). Elements of World Knowledge (EWoK): A Cognition-Inspired Framework for Evaluating Basic World Knowledge in Language Models. Transactions of the Association for Computational Linguistics.
Javier Conde, María Grandury, Tairan Fu, Carlos Arriaga, Gonzalo Martínez, Thomas Clark, Sean Trott, Clarence Gerald Green, Pedro Reviriego, & Marc Brysbaert (2025). Adding LLMs to the psycholinguistic norming toolbox: A practical guide to getting the most out of human ratings. arXiv preprint arXiv:2509.14405.
Thomas Clark, Jacob Hoover Vigly, Edward Gibson, & Roger Levy (2025). A model of approximate and incremental noisy-channel language processing. Proceedings of the Annual Meeting of the Cognitive Science Society.
Thomas Clark, Edward Gibson, & Roger Levy (2024). Inferring errors and intended meanings with a generative model of language production in aphasia. Proceedings of the Annual Meeting of the Cognitive Science Society.
Thomas Hikaru Clark, Clara Meister, Tiago Pimentel, Michael Hahn, Ryan Cotterell, Richard Futrell, & Roger Levy (2023). A cross-linguistic pressure for Uniform Information Density in word order. Transactions of the Association for Computational Linguistics.
Thomas Clark, Ethan Gotlieb Wilcox, Edward Gibson, & Roger Levy (2022). Evidence for availability effects on speaker choice in the Russian comparative alternation. Proceedings of the Annual Meeting of the Cognitive Science Society.
Clara Meister, Tiago Pimentel, Thomas Clark, Ryan Cotterell, & Roger Levy (2022). Analyzing wrap-up effects through an information-theoretic lens. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers).
Zaiqiao Meng, Fangyu Liu, Thomas Clark, Ehsan Shareghi, & Nigel Collier (2021). Mixture-of-partitions: Infusing large biomedical knowledge graphs into BERT. Proceedings of the 2021 conference on empirical methods in natural language processing.
Thomas Clark, Costanza Conforti, Fangyu Liu, Zaiqiao Meng, Ehsan Shareghi, & Nigel Collier (2021). Integrating transformers and knowledge graphs for Twitter stance detection. Proceedings of the seventh workshop on noisy user-generated text (W-NUT 2021).
Napoleon Katsos, Ema Banerjee, Yin Jue Chang, Thomas Clark, Joe Cowan, Thomas R Williamson, & Zuzanna Witkowska (2021). Experimental Pragmatics: The Making of a Cognitive Science. Elsevier.

Oral Presentations

“Resource-Rational Noisy-Channel Language Processing: Testing the Effect of Algorithmic Constraints on Inferences”, 2025 Conference on Empirical Methods in Natural Language Processing.
“A Model of Approximate and Incremental Noisy-Channel Language Processing”, 47th Annual Meeting of the Cognitive Science Society.
“Evidence for an Availability-Based Production Account of the Russian Comparative Alternation via Corpus Analysis”, 35th Annual Conference on Human Sentence Processing.

Poster Presentations

“A Model of Approximate and Incremental Noisy-Channel Language Processing”, 47th Annual Meeting of the Cognitive Science Society (upcoming).
“Modeling Noisy-Channel Language Processing with Incremental and Approximate Probabilistic Inference”, 38th Annual Conference on Human Sentence Processing.
“Meaning distinctiveness predicts sentence memorability”, 38th Annual Conference on Human Sentence Processing.
“Inferring Errors and Intended Meanings with a Generative Model of Language Production in Aphasia”, 46th Annual Meeting of the Cognitive Science Society.
“A Cross-Linguistic Pressure for Uniform Information Density in Word Order”, EMNLP 2023.
“Context-sensitive features predict sentence memorability in the absence of memorable words”, 45th Annual Meeting of the Cognitive Science Society.
“Word Frequency Predicts Word Errors in Stroke-Induced Aphasia”, 36th Annual Conference on Human Sentence Processing.
“Evidence for Syntax-Lexicon Trade-off in Stroke-Induced Aphasia Patients”, 36th Annual Conference on Human Sentence Processing.
“A Cross-Linguistic Pressure for Uniform Information Density in Word Order”, 36th Annual Conference on Human Sentence Processing.
“Evidence for Availability Effects on Speaker Choice in the Russian Comparative Alternation”, 44th Annual Meeting of the Cognitive Science Society.

Education

I am currently a PhD candidate at MIT in the department of Brain and Cognitive Sciences, where I am a member of TedLab and the Computational Psycholinguistics Lab. I received my undergraduate degree in Computer Science from Princeton University, where I also earned certificates in Linguistics and Russian Language & Culture. After college, I earned an M.Ed. from the University of Notre Dame as part of the ACE Teaching Fellows 25th Cohort; I taught HS Computer Science and Math in Jacksonville, FL. Afterwards, I returned to grad school for an MPhil in Theoretical and Applied Linguistics from the University of Cambridge, where I was involved in the Language Technology Lab and continued on to a PhD in a different city named Cambridge.

Other Experience

Before starting my PhD, I interned at Vimeo on the Machine Learning Research team and at IBM Watson on the Speech to Text team. Previously, I have done iOS development for the Paideia Institute in Rome, Italy, and have done volunteer service projects in Russia and Japan. During the summer of 2021, I was an instructor for a summer startup camp at the Cambridge Center for International Research, teaching machine learning and data science principles to students from around the world.