Help or Hinder: Bayesian Models of Social Goal Inference. - Tomer D. Ullman; Chris L. Baker; Owen Macindoe; Owain Evans; Noah D. Goodman; Joshua B. Tenenbaum (NIPS, 2009)

Forward Physics: How people learn and generalize novel dynamical models. - Tomer D. Ullman; Noah D. Goodman; Josh Tenenbaum 001 (CogSci, 2011)

Computational Models of Intuitive Physics. - Peter W. Battaglia; Tomer D. Ullman; Joshua B. Tenenbaum; Adam Sanborn; Kenneth D. Forbus; Tobias Gerstenberg; David A. Lagnado (CogSci, 2012)

Probabilistic generative models for counterfactual reasoning and blame attribution. - John McCoy; Tomer D. Ullman; Andreas Stuhlmüller; Tobias Gerstenberg; Joshua B. Tenenbaum (CogSci, 2012)

Sticking to the Evidence? A computational and behavioral case study of micro-theory change in the domain of magnetism. - Elizabeth Bonawitz; Tomer D. Ullman; Alison Gopnik; Joshua B. Tenenbaum (ICDL-EPIROB, 2012)

Minimal Nativism: How does cognitive development get off the ground? - Tomer D. Ullman; Joshua B. Tenenbaum; Noah D. Goodman; Shimon Ullman; Elizabeth S. Spelke (CogSci, 2013)

Wins above replacement: Responsibility attributions as counterfactual replacements. - Tobias Gerstenberg; Tomer D. Ullman; Max Kleiman-Weiner; David A. Lagnado; Joshua B. Tenenbaum (CogSci, 2014)

Learning physical theories from dynamical scenes. - Tomer D. Ullman; Andreas Stuhlmüller; Noah D. Goodman; Joshua B. Tenenbaum (CogSci, 2014)

Outcome or Strategy? A Bayesian Model of Intelligence Attribution. - Marta Kryven; Tomer D. Ullman; William Cowan; Josh Tenenbaum 001 (CogSci, 2016)

Coalescing the Vapors of Human Experience into a Viable and Meaningful Comprehension. - Tomer D. Ullman; Max H. Siegel; Josh Tenenbaum 001; Samuel Gershman (CogSci, 2016)

The Pragmatics of Spatial Language. - Tomer D. Ullman; Yang Xu 023; Noah D. Goodman (CogSci, 2016)

Building Machines That Learn and Think Like People. - Brenden M. Lake; Tomer D. Ullman; Joshua B. Tenenbaum; Samuel J. Gershman (CoRR, 2016)

Thinking and Guessing: Bayesian and Empirical Models of How Humans Search. - Marta Kryven; Tomer D. Ullman; William Cowan; Josh Tenenbaum 001 (CogSci, 2017)

What's worth the effort: Ten-month-old infants infer the value of goals from the costs of actions. - Shari Liu; Tomer D. Ullman; Josh Tenenbaum 001; Elizabeth S. Spelke (CogSci, 2017)

Weight matters: The role of physical weight in non-physical language across age and culture. - Tomer D. Ullman; Santiago Alonso-Diaz; Stephen Ferrigno; Sarina Zahid; Celeste Kidd (CogSci, 2017)

A Compositional Object-Based Approach to Learning Physical Dynamics. - Michael Chang 003; Tomer D. Ullman; Antonio Torralba 001; Joshua B. Tenenbaum (ICLR (Poster), 2017)

Models of Human Scientific Discovery. - Robert L. Goldstone; Alison Gopnik; Paul Thagard; Tomer D. Ullman (CogSci, 2018)

Moral Dynamics: A Computational Model of Moral Judgment. - Felix Sosa; Tomer D. Ullman; Samuel Gershman; Josh Tenenbaum 001; Tobias Gerstenberg (CogSci, 2018)

People's perception of others' risk preferences. - Shari Liu; John McCoy; Tomer D. Ullman (CogSci, 2019)

Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects. - Tomer D. Ullman; Eliza Kosoy; Ilker Yildirim; Amir Arsalan Soltani; Max H. Siegel; Josh Tenenbaum 001; Elizabeth S. Spelke (CogSci, 2019)

Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations. - Kevin Smith 003; Lingjie Mei; Shunyu Yao; Jiajun Wu 001; Elizabeth S. Spelke; Josh Tenenbaum 001; Tomer D. Ullman (NeurIPS, 2019)

Sticking to the Evidence? A Behavioral and Computational Case Study of Micro-Theory Change in the Domain of Magnetism. - Elizabeth Bonawitz; Tomer D. Ullman; Sophie Bridgers; Alison Gopnik; Joshua B. Tenenbaum (Cogn. Sci., 2019)

The Origins of Common Sense in Humans and Machines. - Kevin Smith 003; Eliza Kosoy; Alison Gopnik; Deepak Pathak; Alan Fern; Josh Tenenbaum 001; Tomer D. Ullman (CogSci, 2020)

The fine structure of surprise in intuitive physics: when, why, and how much? - Kevin Smith 003; Lingjie Mei; Shunyu Yao; Jiajun Wu 001; Elizabeth S. Spelke; Josh Tenenbaum 001; Tomer D. Ullman (CogSci, 2020)

Look before you leap: Quantitative tradeoffs between peril and reward in action understanding. - Nensi Gjata; Tomer D. Ullman; Elizabeth S. Spelke; Shari Liu (CogSci, 2020)

Adventures in Flatland: Perceiving Social Interactions Under Physical Dynamics. - Tianmin Shu; Marta Kryven; Tomer D. Ullman; Josh Tenenbaum 001 (CogSci, 2020)

Loopholes, a Window into Value Alignment and the Learning of Meaning. - Sophie Bridgers; Laura Schulz; Tomer D. Ullman (CogSci, 2021)

Unsupervised Discovery of 3D Physical Objects from Video. - Yilun Du; Kevin A. Smith 001; Tomer D. Ullman; Joshua B. Tenenbaum; Jiajun Wu 001 (ICLR, 2021)

AGENT: A Benchmark for Core Psychological Reasoning. - Tianmin Shu; Abhishek Bhandwaldar; Chuang Gan 001; Kevin A. Smith 001; Shari Liu; Dan Gutfreund; Elizabeth S. Spelke; Joshua B. Tenenbaum; Tomer D. Ullman (ICML, 2021)

Temporal and Object Quantification Networks. - Jiayuan Mao; Zhezheng Luo; Chuang Gan 001; Joshua B. Tenenbaum; Jiajun Wu 001; Leslie Pack Kaelbling; Tomer D. Ullman (IJCAI, 2021)

A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics. - Kai Xu 016; Akash Srivastava; Dan Gutfreund; Felix Sosa; Tomer D. Ullman; Josh Tenenbaum 001; Charles Sutton (NeurIPS, 2021)

Plans or Outcomes: How Do We Attribute Intelligence to Others? - Marta Kryven; Tomer D. Ullman; William Cowan; Joshua B. Tenenbaum (Cogn. Sci., 2021)

Adults' Evaluations of Rote and Reflective Teachers. - Ilona Bass; Elizabeth Bonawitz; Tomer D. Ullman (CogSci, 2022)

People's evaluation of programs that drive agents' behavior. - Eric J. Bigelow; Tomer D. Ullman (CogSci, 2022)

Combining mental simulation and abstract reasoning explains people's reaction time in an intuitive physics task. - Felix A. Sosa; Samuel Gershman; Tomer D. Ullman (CogSci, 2022)

What Could Go Wrong: Adults and Children Calibrate Predictions and Explanations of Others' Actions Based on Relative Reward and Danger. - Nensi Gjata; Tomer D. Ullman; Elizabeth S. Spelke; Shari Liu (Cogn. Sci., 2022)

Testing Relational Understanding in Text-Guided Image Generation. - Colin Conwell; Tomer D. Ullman (CoRR, 2022)

Type theory in human-like learning and inference. - Felix A. Sosa; Tomer D. Ullman (CoRR, 2022)

Skirting the Sacred: Moral Violations Make Intentional Misunderstandings Worse. - Kiera Parece; Sophie Bridgers; Laura Schulz; Tomer D. Ullman (CogSci, 2023)

Comparing the Evaluation and Production of Loophole Behavior in Humans and Large Language Models. - Sonia K. Murthy; Kiera Parece; Sophie Bridgers; Peng Qian; Tomer D. Ullman (EMNLP (Findings), 2023)

Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks. - Tomer D. Ullman (CoRR, 2023)

MMToM-QA: Multimodal Theory of Mind Question Answering. - Chuanyang Jin; Yutong Wu; Jing Cao; Jiannan Xiang; Yen-Ling Kuo; Zhiting Hu; Tomer D. Ullman; Antonio Torralba 001; Joshua B. Tenenbaum; Tianmin Shu (ACL (1), 2024)

In-Context Learning Dynamics with Random Binary Sequences. - Eric J. Bigelow; Ekdeep Singh Lubana; Robert P. Dick; Hidenori Tanaka; Tomer D. Ullman (ICLR, 2024)

Relations, Negations, and Numbers: Looking for Logic in Generative Text-to-Image Models. - Colin Conwell; Rupert Tawiah-Quashie; Tomer D. Ullman (CoRR, 2024)

The Illusion-Illusion: Vision Language Models See Illusions Where There are None. - Tomer D. Ullman (CoRR, 2024)

Approximate planning in spatial search. - Marta Kryven; Suhyoun Yu; Max Kleiman-Weiner; Tomer D. Ullman; Joshua B. Tenenbaum (PLoS Comput. Biol., 2024)

Teaching Without Thinking: Negative Evaluations of Rote Pedagogy. - Ilona Bass; Cristian Espinoza; Elizabeth Bonawitz; Tomer D. Ullman (Cogn. Sci., 2024)

Forking Paths in Neural Text Generation. - Eric J. Bigelow; Ari Holtzman; Hidenori Tanaka; Tomer David Ullman (ICLR, 2025)

One fish, two fish, but not the whole sea: Alignment reduces language models' conceptual diversity. - Sonia K. Murthy; Tomer D. Ullman; Jennifer Hu 001 (NAACL (Long Papers), 2025)

Shades of Zero: Distinguishing Impossibility from Inconceivability. - Jennifer Hu 001; Felix Sosa; Tomer D. Ullman (CoRR, 2025)

Re-evaluating Theory of Mind evaluation in large language models. - Jennifer Hu 001; Felix Sosa; Tomer D. Ullman (CoRR, 2025)

Inside you are many wolves: Using cognitive models to interpret value trade-offs in LLMs. - Sonia K. Murthy; Rosie Zhao; Jennifer Hu 001; Sham M. Kakade; Markus Wulfmeier; Peng Qian; Tomer D. Ullman (CoRR, 2025)

Emergence of Hierarchical Emotion Organization in Large Language Models. - Bo Zhao 028; Maya Okawa; Eric J. Bigelow; Rose Yu; Tomer D. Ullman; Ekdeep Singh Lubana; Hidenori Tanaka (CoRR, 2025)