Personal profile
Research Interests
Jon Willits studies language and learning in infants, children, adults, and machines. His research uses computational, neurobiological, experimental, and naturalistic methods to better understand how people and machines learn, represent, and use languages and other forms of complex knowledge, especially word meanings and semantic knowledge.
Creative/Performing Interests
- Cognitive Development
- Word learning, Semantic Development, and Knowledge Acquisition
- Computational Modeling, Neural Networks, Natural Language Processing, and Data Science
Education/Academic qualification
PhD, University of Wisconsin-Madison
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Collaborations and top research areas from the last five years
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Large language models and the N400
Chia, L. K. A. & Willits, J. A., Jan 2025, In: Psychology of Learning and Motivation - Advances in Research and Theory. p. 1-43 43 p.Research output: Contribution to journal › Article › peer-review
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Success and failure of compositional generalisation in distributional models of language
Mao, S., Huebner, P. & Willits, J., 2025, In: Language, Cognition and Neuroscience. 40, 3, p. 413-441 29 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Analogical inference from distributional structure: What recurrent neural networks can tell us about word learning[Formula presented]
Huebner, P. A. & Willits, J. A., Sep 15 2023, In: Machine Learning with Applications. 13, 100478.Research output: Contribution to journal › Article › peer-review
Open Access -
Spatial Versus Graphical Representation of Distributional Semantic Knowledge
Mao, S., Huebner, P. A. & Willits, J. A., Nov 13 2023, In: Psychological review. 131, 1, p. 104-137 34 p.Research output: Contribution to journal › Article › peer-review
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Using known words to learn more words: A distributional model of child vocabulary acquisition
Flores, A. Z., Montag, J. L. & Willits, J. A., Oct 2023, In: Journal of Memory and Language. 132, 104446.Research output: Contribution to journal › Article › peer-review
Open Access