About
I am the Morris Kahn Associate Professor of Psychology in the Department of Psychology at Harvard University.
I head the Computation, Cognition, and Development lab,
with a focus on intuitive theories and people's common-sense reasoning about physics and psychology.
I'm also an affiliate of the Kempner Institute for the Study of Natural and Artificial Intelligence.
Teaching
Decisions, Big and Small: The Cognitive Science of Making Up Your Mind
PSY1322
A general-audience class geared towards 2nd to 4th year undergraduates, with a background in cognitive science, CS, economics, or neuroscience.
Imagination, Pretense, and Make-Believe Worlds
PSY1340
An advanced seminar. Geared towards senior undergraduates or first-year graduate students, looking to do research on imagery and imagination.
Publications
2025
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Bridgers, S., Qian, P., Parece, K., Taliaferro, M., Schulz, L., and Ullman, T. D. (2025) Loopholes: A window into value alignment and the communication of meaning. Cognition.
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Balaban, H., and Ullman, T. D. (2025) The capacity limits of moving objects in the imagination. Nature Communications.
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Balaban, H., and Ullman, T. D. (2025) Physics versus graphics as an organizing dichotomy in cognition. Trends in Cognitive Sciences.
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Wang, Y., and Ullman, T. D. (2025) Resource bounds on mental simulations: Evidence from a liquid-reasoning task. JEP: General.
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Bass, I., Colantonio, J., Aboody, R., Wong, M., Ullman, T., and Bonawitz, E. (2025) Children's sensitivity to automatic behavior relates to pedagogical reasoning and Theory of Mind. Frontiers in Developmental Psychology.
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Bridgers, S.*, Parece*, K., Iwasaki, I., Broski, A., Schulz, L., and Ullman, T.D. (2025) Learning Loopholes: The Development of Intentional Misunderstandings in Children. Child Development.
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Sosa, F. A., Gershman, S. J., and Ullman, T. D. (2025) Blending simulation and abstraction for physical reasoning. Cognition.
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Hu, J., Sosa, F., and Ullman, T.D. (2025) Re-evaluating Theory of Mind evaluation in large language models. Philosophical Transactions B.
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Hu, J., Sosa, F., and Ullman, T.D. (2025) Shades of Zero: Distinguishing Impossibility from Inconceivability. Journal of Memory and Language.
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Murthy, S. K., Zhao, R., Hu, J., Kakade, S., Wulfmeier, M., Qian, P., and Ullman, T.D. (2025) Inside you are many wolves: Using cognitive models to interpret value trade-offs in LLMs. CoLM workshop (Spotlight presentation)
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Zhao, B., Okawa, M., Bigelow, E. J., Yu, R., Ullman, T., Lubana, E. S., and Tanaka, H.(2025) Emergence of Hierarchical Emotion Organization in Large Language Models. Preprint
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Bigelow, E., Holtzman, A., Tanaka, H.*, and Ullman, T.D.* (2025) Forking Paths in Neural Text Generation. ICLR
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Murthy, S., Ullman, T.D., and Hu, J. (2025) One fish, two fish, but not the whole sea: Alignment reduces language models' conceptual diversity. NAACL
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Hu, J., Sosa, F., and Ullman, T. D. (2025) Making sense of nonsense. Proceedings of the 47th Annual Meeting of the Cognitive Science Society
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Bhattacharya, A., Hu, J., and Ullman, T. D. (2025) The Uncanny Valley meets the Humorous Hill: Things are funny when they match a pattern but fall short on quality. Proceedings of the 47th Annual Meeting of the Cognitive Science Society
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Parece, K., Ullman, T. D., and Schulz, L., (2025) Intuitions about prosocial backfiring: Four to seven-year olds' understanding of when helping might cause offense. Proceedings of the 47th Annual Meeting of the Cognitive Science Society
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Chu, J., O'Keeffe, M., Liu, S. K., Bonawitz, E., and Ullman, T. D. (2025) Stumped! Learning to think outside the box in 3-7 year old children. Proceedings of the 47th Annual Meeting of the Cognitive Science Society
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Xiang, Y., Bigelow, E., Gerstenberg, T., Ullman, T. D., and Gershman, S. (2025) Language models assign responsibility based on actual rather than counterfactual contributions. Proceedings of the 47th Annual Meeting of the Cognitive Science Society
2024
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Ullman, T.D., and Bass, I. (2024). The Detection of Automatic Behavior in Other People. American Psychologist.
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Qian, P., Bridgers, S. E. C., Taliaferro, M., Parece, K., and Ullman, T. (2024). Ambivalence by Design: A Computational Account of Loopholes. Cognition.
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Balaban, H., and Ullman, T.D. (2024) The Capacity Limits of Mental Simulation. psyArxiv preprint
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Conwell, C., Tawiah-Quashie, R., and Ullman, T.D. (2024) Relations, Negations, and Numbers: Looking for Logic in Generative Text-to-Image Models. arxiv preprint
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Qian, P., and Ullman, T.D. (2024) Shape Guides Visual Pretense. psyArxiv preprint
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Ullman, T.D. (2024) The Ilusion Illusion: Vision Language Models See Illusions Where There are None. psyArxiv preprint
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Ullman, T.D. and Bridgers, S. (2024) Genies, lawyers, and smart-asses: Extending proxy failures to intentional misunderstandings. Behavioral and Brain Sciences
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Bass, I., Espinoza, C., Bonawitz, E., and Ullman, T. D. (2024) Teaching without thinking: Negative evaluations of rote pedagogy. Cognitive Science
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Balaban, H., Smith, K., Tenenbaum, J., and Ullman, T.D. (2024). Electrophysiology reveals that intuitive physics guides visual tracking and working memory. Open Mind.
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Kryven, M., Yu, S., Kleiman-Weiner, M., Ullman, T., and Tenenbaum, J. (2024). Approximate planning in spatial search. PLOS Computational Biology.
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Bonawitz, E., and Ullman, T. D. (2024) Bayesian models of cognitive development. Bayesian Models of Cognition: Reverse Engineering the Mind
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Smith, K. A., Hamrick, J. B., Sanborn, Adam N., Battaglia, P. W., Gerstenberg, T., Ullman, T. D. and Tenenbaum, J. B. (2024) Intuitive physics as probabilistic inference. Bayesian Models of Cognition: Reverse Engineering the Mind
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Jara-Ettinger, J., Baker, C., Ullman, T. D. and Tenenbaum, J. B. (2024) Theory of mind and inverse decision-making. Bayesian Models of Cognition: Reverse Engineering the Mind
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Jin, C., Wu, Y., Cao, J., Xiang, J., Kuo, Y.L., Hu, Z., Ullman, T., Torralba, A., Tenenbaum, J.B. and Shu, T. (2024) Mmtom-qa: Multimodal theory of mind question answering. ACL
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Chu, J., Hu, J., and Ullman, T.D. (2024) The Task Task: Creative problem generation in humans and language models. Proceedings of the 46th Annual Meeting of the Cognitive Science Society
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Hu, J., and Sosa, F., and Ullman, T.D. (2024) Shades of Zero: Distinguishing impossibility from inconceivability. Proceedings of the 46th Annual Meeting of the Cognitive Science Society
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Parece, K., and Bridgers, S., and Ullman, T.D., and Schulz, L. (2024) Exploring Loophole Behavior: A Comparative Study of Autistic and Non-Autistic Populations. Proceedings of the 46th Annual Meeting of the Cognitive Science Society
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Jonusaite, S. and Ullman, T.D., (2024). The Invisible Hand as an Intuitive Sociological Explanation. Journal of Experimental Social Psychology.
2023
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Murthy, S., Parece, K., Bridgers, S., Qian, P., and Ullman, T.D. (2023). Comparing the Evaluation and Production of Loophole Behavior in Humans and Large Language Models. Findings of the Association for Computational Linguistics: EMNLP
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Bigelow, E. J., Lubana, E. S., Dick, R. P., Tanaka, H., and Ullman, T. D. (2023). In-Context Learning Dynamics with Random Binary Sequences. arXiv preprint
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Parece, K., Bridgers, S. E. C., Qian, P., Schulz, L., and Ullman, T. (2023). Skirting the Sacred: Moral Contexts Increase the Cost of Intentional Misunderstandings. psyarxiv preprint.
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De Freitas, J., Uğuralp, A. K., Oğuz-Uğuralp, Z., Paul, L. A., Tenenbaum, J., & Ullman, T. D. (2023). Self-orienting in human and machine learning. Nature Human Behavior.
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Bridgers, S. E. C., Taliaferro, M., Parece, K., Schulz, L., & Ullman, T. (2023). Loopholes: A window into value alignment and the communication of meaning. psyarxiv preprint.
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Rule, J., Goddu, M., Chu, J., Pinter, V., Reagan, E. R., Bonawitz, E., & Ullman, T. (2023). Fun isn’t easy: Children choose more difficult options when playing for fun vs. trying to win. psyarxiv preprint.
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Paul, L. A., Ullman, T., De Freitas, J., & Tenenbaum, J. (2023). Reverse-engineering the Self. psyarxiv preprint.
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Wang, Y., and Ullman, T. D. (2023). Resource bounds on mental simulations: Evidence from a fluid-reasoning task. psyarxiv preprint.
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Li, Y., Wang, Y., Boger, T., Smith, K. A., Gershman, S. J., & Ullman, T. D. (2023). An approximate representation of objects underlies physical reasoning. JEP: General
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Gershman, S. and Ullman, T.D., (2023). Causal Implicatures from Correlational Statements. PLOS ONE.
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Bigelow, E. J., McCoy,* J., & Ullman, T.* (2023). Non-Commitment in Mental Imagery. Cognition.
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Burnell, R., Schellaert, W., Burden, J., Ullman, T.D., Martinez-Plumed, F., Tenenbaum, J.B., Rutar, D., Cheke, L.G., Sohl-Dickstein, J., Mitchell, M. and Kiela, D. (2023). Rethink reporting of evaluation results in AI. Science
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Boger, T., & Ullman, T. (2023). What is “where”: Physical reasoning informs object location. Open Mind.
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Ullman, T. (2023). Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks. arXiv preprint.
2022
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Shu, T., Magaro, A., Kryven, M., Ullman, T., & Tenenbaum, J. (2022). Social Attribution Guides Similarity Judgment of Abstract Scenes. Journal of Vision.
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Liu, S., Pepe, B., Ganesh Kumar, M., Ullman, T. D., Tenenbaum, J. B., & Spelke, E. S. (2022). Dangerous ground: One-year-old infants are sensitive to peril in other agents’ action plans. Open Mind.
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De Freitas, J., Uğuralp, A. K., Uğuralp, Z., Kim, P., & Ullman, T. D. (2023). Summarizing the Mental Customer Journey. Harvard Business School Working Paper.
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Balaban, H., Smith, K. A., Ullman, T. D., & Tenenbaum, J. B. (2022). Using EEG to uncover the dynamics of physical expectation violation and resolution. Journal of Vision.
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Sosa, F. A., & Ullman, T. (2022). Type theory in human-like learning and inference. arXiv.
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Bass, L., Smith, K, Bonawitz, E., and Ullman, T.D., (2022) Partial Mental Simulation Explains Fallacies in Physical Reasoning. Cognitive Neuropsychology.
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Gjata, N. N., Ullman, T. D., Spelke, E. S., and Liu, S. (2022). What could go wrong: adults and children calibrate predictions and explanations of others' actions based on relative reward and danger. Cognitive Science.
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Conwell, C., and Ullman, T.D., (2022). Testing Relational Understanding in Text-Guided Image Generation. arxiv.
2021
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Bridgers, S., Schulz, L.E., and Ullman, T.D. (2021). Loopholes, a Window into Value Alignment and the Learning of Meaning. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society.
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Mao, J., Luo, Z., Gan, C., Tenenbaum, J.B., Wu, J., Kaelbling, J.P., and Ullman, T.D. (2021). Temporal and Object Quantification Networks. Thirtieth International Joint Conference on Artificial Intelligence (IJCAI).
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Sosa, F. A., Ullman, T., Tenenbaum, J. B., Gershman, S. J., & Gerstenberg, T. (2021). Moral dynamics: Grounding moral judgment in intuitive physics and intuitive psychology. Cognition.
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Ullman, T. D. (2021). What are you talking about? Nature Human Behaviour.
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Shu, T., Bhandwaldar, A., Gan, C., Smith, K.A., Liu, S., Gutfreund, D., Spelke, E., Tenenbaum, J.B. and Ullman, T.D. (2021). AGENT: A Benchmark for Core Psychological Reasoning. Thirty-eighth International Conference on Machine Learning (ICML).
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Du, Y., Smith, K., Ullman, T.D., Tenenbaum, J.B., and Wu, J. (2021). Unsupervised Discovery of 3D Physical Objects From Video. International Conference on Learning Representations (ICLR).
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Kryven, M., Ullman, T.D., Cowan, W., and Tenenbaum, J.B., (2021) Plans or Outcomes: How do we attribute intelligence to others? Cognitive Science.
2020
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Ullman, T. D., and Tenenbaum, J. B. (2020). Bayesian Models of Conceptual Development: Learning as Building Models of the World. Annual Review of Developmental Psychology.
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Zimmerman, S, and Ullman, T.D. (2020) Models of Transformative Decision Making, Transformative Experience: New Philosophical Essays.
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Smith, K. A., Mei, L., Yao, S., Wu, J., Spelke, E., Tenenbaum, J. B., and Ullman, T. D. (2020). The fine structure of surprise in intuitive physics: when, why, and how much? Proceedings of the 42nd Annual Meeting of the Cognitive Science Society.
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Ullman, T.D. (2020). Heroes of our own story: Self-image and rationalizing in thought experiments. Behavioral and Brain Sciences
2019
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McCoy, J. and Ullman, T. (2019) Transformative Decisions and Their Discontents. Rivista Internazionale di Filosofia e Psicologia, 10(3), 339 - 345.
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Smith, K.*, Mei, L.*, Yao, S., Wu, J., Spelke, E., Tenenbaum, J.B., and Ullman, T.D., (2019) Modeling expectation violation in intuitive physics with coarse probabilistic object representations. Advances in Neural Information Processing Systems
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Bonawitz E., Ullman, T.D., Gopnik, A. and Tenenbaum, J.B. (2019), Sticking to the evidence? A Computational and behavioral case study of micro-theory change in the domain of magnetism. Cognitive Science.
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McCoy, J.P., and Ullman, T.D. (2019), Judgments of effort for magical violations of intuitive physics. PLOS ONE
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McCoy, J.P.*, Paul, LA*, and Ullman, T.D.* (2019), Modal Prospection. Metaphysics and Cognitive Science, eds. Alvin Goldman and Brian McLaughlin. Oxford University Press (US)
2018
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McCoy, J.P., and Ullman, T.D. (2018), A Minimal Turing Test. Journal of Experimental Social Psychology
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Gerstenberg, T., Ullman, T.D., Nagel, J., Kleiman-Weiner, M., Lagnado, D., and Tenenbaum, J.B. (2018), Lucky or clever? From changed expectations to attributions of responsibility. Cognition.
2017
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Ullman, T. D., Spelke, E.S., Battaglia, P. and Tenenbaum, J.B. (2017), Mind Games: Game Engines as an Architecture for Intuitive Physics. Trends in Cognitive Science
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Liu, S., Ullman, T. D., Tenenbaum, J.B., and Spelke, E.S., (2017), Ten-month-old infants infer the value of goals from the costs of actions. Science
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Ullman, T. D., Stuhlmüller, A., Goodman, N.D. and Tenenbaum, J.B. (2017), Learning physical parameters from dynamic scenes. Cognitive Psychology
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Ullman, T. D., Alonso-Diaz, S., Ferringo, S., Zahid, S. and Kidd, C. (2017), Weight matters: The role of physical weight in non-physical language across age and culture. Proceedings of the 39th Annual Meeting of the Cognitive Science Society
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Chang, M. B., Ullman, T. D., Torralba, A., and Tenenbaum, J. B. (2017), A compositional object-based approach to learning physical dynamics. International Conference on Learning Representations (ICLR)
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Liu, S., Ullman, T. D., Tenenbaum, J. B., and Spelke, E. S. (2017). What’s worth the effort: Ten-month-old infants infer the value of goals from the costs of actions. Proceedings of the 39th Annual Meeting of the Cognitive Science Society
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Kryven, M., Ullman, T. D., Cowan, W., and Tenenbaum, J. B. (2017). Thinking and guessing: Bayesian and empirical models of how humans search. Proceedings of the 39th Annual Meeting of the Cognitive Science Society
2016 and earlier
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Lake, B. M., Ullman, T. D., Tenenbaum, J. B., and Gershman, S. J. (2016), Building machines that learn and think like people. Behavioral and Brain Sciences
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T. D. Ullman, Y. Xu and N. D. Goodman (2016), The Pragmatics of Spatial Language. Proceedings of the 38th Annual Conference of the Cognitive Science Society.
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M. Kryven, T. D. Ullman, W. Cowan and J. B. Tenenbaum (2016), Outcome or Strategy? A Bayesian Model of Intelligence Attribution. Proceedings of the 38th Annual Conference of the Cognitive Science Society.
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T. D. Ullman, M. Siegel, J. B. Tenenbaum and S. J. Gershman (2016), Coalescing the vapors of human experience into a viable and meaningful comprehension. Proceedings of the 38th Annual Conference of the Cognitive Science Society.
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T. Gerstenberg, T. D. Ullman, M. Kleiman-Weiner, D. A. Lagnado and J. B. Tenenbaum (2014), Wins above replacement: Responsibility attributions as counterfactual replacements. Proceedings of the Thirty-Sixth Annual Conference of the Cognitive Science society.
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T. D. Ullman, A. Stuhlmüller, N. D. Goodman, J. B. Tenenbaum (2014), Learning physics from dynamical scenes. Proceedings of the Thirty-Sixth Annual Conference of the Cognitive Science society.
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J. K. Hamlin, T. D. Ullman, J. B. Tenenbaum, N. D. Goodman and C. L. Baker (2013), The mentalistic basis of core social cognition: Experiments in preverbal infants and a computational model. Developmental Science.
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E. B. Bonawitz, T. D. Ullman, A. Gopnik and J. B. Tenenbaum (2012), Sticking to the evidence? A computational and behavioral case study of micro-theory change in the domain of magnetism. ICDL (best paper award: experiment combined with computational model).
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T. D. Ullman, N. D. Goodman and J. B. Tenenbaum (2012), Theory learning as stochastic search in the language of thought. Cognitive Development.
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T. D. Ullman*, J. M. McCoy*, A. Stuhlmüller, T. Gerstenberg and J. B. Tenenbaum (2012), Why blame Bob? Probabilistic generative models, counterfactual reasoning, and blame attribution. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science society.
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N. D. Goodman, T. D. Ullman, and J. B. Tenenbaum (2011), Learning a theory of causality. Psychological Review.
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T. D. Ullman, N. D. Goodman and J. B. Tenenbaum (2010), Theory acquisition as stochastic search. Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society.
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T. D. Ullman, C. L. Baker, O. Macindoe, O. Evans, N. D. Goodman and J. B. Tenenbaum (2010), Help or hinder: Bayesian models of social goal inference. Advances in Neural Information Processing Systems (Vol. 22, pp. 1874-1882).
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N. D. Goodman, T. D. Ullman, and J. B. Tenenbaum (2009), Learning a theory of causality. Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society.