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ORCIDTomer D. Ullman
Person information
- affiliation: Harvard University, Department of Psychology, Cambridge, MA, USA
- affiliation (PhD 2015): Massachusetts Institute of Technology (MIT), Department of Brain and Cognitive Sciences, Cambridge, MA, USA
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2020 – today
- 2024
[i10]Chuanyang Jin, Yutong Wu, Jing Cao, Jiannan Xiang, Yen-Ling Kuo, Zhiting Hu, Tomer D. Ullman, Antonio Torralba, Joshua B. Tenenbaum, Tianmin Shu:
MMToM-QA: Multimodal Theory of Mind Question Answering. CoRR abs/2401.08743 (2024)- 2023
- [c29]Sonia Murthy, Kiera Parece, Sophie Bridgers, Peng Qian, Tomer D. Ullman:
Comparing the Evaluation and Production of Loophole Behavior in Humans and Large Language Models. EMNLP (Findings) 2023: 4010-4025 - [i9]Tomer D. Ullman:
Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks. CoRR abs/2302.08399 (2023) - [i8]Eric J. Bigelow, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tomer D. Ullman:
In-Context Learning Dynamics with Random Binary Sequences. CoRR abs/2310.17639 (2023) - 2022
- [j3]Nensi Gjata, Tomer D. Ullman, Elizabeth S. Spelke, Shari Liu
:
What Could Go Wrong: Adults and Children Calibrate Predictions and Explanations of Others' Actions Based on Relative Reward and Danger. Cogn. Sci. 46(7) (2022) - [e1]José Hernández-Orallo, Lucy Cheke, Joshua B. Tenebaum, Tomer D. Ullman, Fernando Martínez-Plumed, Danaja Rutar, John Burden, Ryan Burnell, Wout Schellaert:
Proceedings of the Workshop on AI Evaluation Beyond Metrics co-located with the 31st International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2022), Vienna, Austria, July 25th, 2022. CEUR Workshop Proceedings 3169, CEUR-WS.org 2022 [contents] - [i7]Colin Conwell, Tomer D. Ullman:
Testing Relational Understanding in Text-Guided Image Generation. CoRR abs/2208.00005 (2022) - [i6]Felix A. Sosa, Tomer D. Ullman:
Type theory in human-like learning and inference. CoRR abs/2210.01634 (2022) - 2021
- [j2]Marta Kryven, Tomer D. Ullman, William Cowan, Joshua B. Tenenbaum:
Plans or Outcomes: How Do We Attribute Intelligence to Others? Cogn. Sci. 45(9) (2021) - [c28]Yilun Du, Kevin A. Smith, Tomer D. Ullman, Joshua B. Tenenbaum, Jiajun Wu:
Unsupervised Discovery of 3D Physical Objects from Video. ICLR 2021 - [c27]Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin A. Smith, Shari Liu, Dan Gutfreund, Elizabeth S. Spelke, Joshua B. Tenenbaum, Tomer D. Ullman:
AGENT: A Benchmark for Core Psychological Reasoning. ICML 2021: 9614-9625 - [c26]Jiayuan Mao, Zhezheng Luo, Chuang Gan, Joshua B. Tenenbaum, Jiajun Wu, Leslie Pack Kaelbling, Tomer D. Ullman:
Temporal and Object Quantification Networks. IJCAI 2021: 2804-2811 - [c25]Kai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer D. Ullman, Josh Tenenbaum, Charles Sutton:
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics. NeurIPS 2021: 2478-2490 - [i5]Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin A. Smith, Shari Liu, Dan Gutfreund, Elizabeth S. Spelke, Joshua B. Tenenbaum, Tomer D. Ullman:
AGENT: A Benchmark for Core Psychological Reasoning. CoRR abs/2102.12321 (2021) - [i4]Jiayuan Mao, Zhezheng Luo, Chuang Gan, Joshua B. Tenenbaum, Jiajun Wu, Leslie Pack Kaelbling, Tomer D. Ullman:
Temporal and Object Quantification Networks. CoRR abs/2106.05891 (2021) - 2020
- [c24]Kevin Smith, Eliza Kosoy, Alison Gopnik, Deepak Pathak, Alan Fern, Josh Tenenbaum, Tomer D. Ullman:
The Origins of Common Sense in Humans and Machines. CogSci 2020 - [c23]Kevin Smith, Lingjie Mei, Shunyu Yao, Jiajun Wu, Elizabeth S. Spelke, Josh Tenenbaum, Tomer D. Ullman:
The fine structure of surprise in intuitive physics: when, why, and how much? CogSci 2020 - [c22]Nensi Gjata, Tomer D. Ullman, Elizabeth S. Spelke, Shari Liu:
Look before you leap: Quantitative tradeoffs between peril and reward in action understanding. CogSci 2020 - [c21]Tianmin Shu, Marta Kryven, Tomer D. Ullman, Josh Tenenbaum:
Adventures in Flatland: Perceiving Social Interactions Under Physical Dynamics. CogSci 2020 - [i3]Yilun Du, Kevin Smith, Tomer D. Ullman, Joshua B. Tenenbaum, Jiajun Wu:
Unsupervised Discovery of 3D Physical Objects from Video. CoRR abs/2007.12348 (2020)
2010 – 2019
- 2019
- [j1]Elizabeth Bonawitz, Tomer D. Ullman, Sophie Bridgers, Alison Gopnik, Joshua B. Tenenbaum:
Sticking to the Evidence? A Behavioral and Computational Case Study of Micro-Theory Change in the Domain of Magnetism. Cogn. Sci. 43(8) (2019) - [c20]Shari Liu, John McCoy, Tomer D. Ullman:
People's perception of others' risk preferences. CogSci 2019: 678-684 - [c19]Tomer D. Ullman, Eliza Kosoy, Ilker Yildirim, Amir Arsalan Soltani, Max H. Siegel, Josh Tenenbaum, Elizabeth S. Spelke:
Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects. CogSci 2019: 3008-3014 - [c18]Kevin Smith, Lingjie Mei, Shunyu Yao, Jiajun Wu, Elizabeth S. Spelke, Josh Tenenbaum, Tomer D. Ullman:
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations. NeurIPS 2019: 8983-8993 - 2018
- [c17]Robert L. Goldstone, Alison Gopnik, Paul Thagard, Tomer D. Ullman:
Models of Human Scientific Discovery. CogSci 2018 - [c16]Felix Sosa, Tomer D. Ullman, Samuel Gershman, Josh Tenenbaum, Tobias Gerstenberg:
Moral Dynamics: A Computational Model of Moral Judgment. CogSci 2018 - 2017
- [c15]Marta Kryven, Tomer D. Ullman, William Cowan, Josh Tenenbaum:
Thinking and Guessing: Bayesian and Empirical Models of How Humans Search. CogSci 2017 - [c14]Shari Liu, Tomer D. Ullman, Josh Tenenbaum, Elizabeth S. Spelke:
What's worth the effort: Ten-month-old infants infer the value of goals from the costs of actions. CogSci 2017 - [c13]Tomer D. Ullman, Santiago Alonso-Diaz, Stephen Ferrigno, Sarina Zahid, Celeste Kidd:
Weight matters: The role of physical weight in non-physical language across age and culture. CogSci 2017 - [c12]Michael Chang, Tomer D. Ullman, Antonio Torralba, Joshua B. Tenenbaum:
A Compositional Object-Based Approach to Learning Physical Dynamics. ICLR (Poster) 2017 - 2016
- [c11]Marta Kryven, Tomer D. Ullman, William Cowan, Josh Tenenbaum:
Outcome or Strategy? A Bayesian Model of Intelligence Attribution. CogSci 2016 - [c10]Tomer D. Ullman, Max H. Siegel, Josh Tenenbaum, Samuel Gershman:
Coalescing the Vapors of Human Experience into a Viable and Meaningful Comprehension. CogSci 2016 - [c9]Tomer D. Ullman, Yang Xu, Noah D. Goodman:
The Pragmatics of Spatial Language. CogSci 2016 - [i2]Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, Samuel J. Gershman:
Building Machines That Learn and Think Like People. CoRR abs/1604.00289 (2016) - [i1]Michael B. Chang, Tomer D. Ullman, Antonio Torralba, Joshua B. Tenenbaum:
A Compositional Object-Based Approach to Learning Physical Dynamics. CoRR abs/1612.00341 (2016) - 2014
- [c8]Tobias Gerstenberg, Tomer D. Ullman, Max Kleiman-Weiner, David A. Lagnado, Joshua B. Tenenbaum:
Wins above replacement: Responsibility attributions as counterfactual replacements. CogSci 2014 - [c7]Tomer D. Ullman, Andreas Stuhlmüller, Noah D. Goodman, Joshua B. Tenenbaum:
Learning physical theories from dynamical scenes. CogSci 2014 - 2013
- [c6]Tomer D. Ullman, Joshua B. Tenenbaum, Noah D. Goodman, Shimon Ullman, Elizabeth S. Spelke:
Minimal Nativism: How does cognitive development get off the ground? CogSci 2013 - 2012
- [c5]Peter W. Battaglia, Tomer D. Ullman, Joshua B. Tenenbaum, Adam Sanborn, Kenneth D. Forbus, Tobias Gerstenberg, David A. Lagnado:
Computational Models of Intuitive Physics. CogSci 2012 - [c4]John McCoy, Tomer D. Ullman, Andreas Stuhlmüller, Tobias Gerstenberg, Joshua B. Tenenbaum:
Probabilistic generative models for counterfactual reasoning and blame attribution. CogSci 2012 - [c3]Elizabeth Bonawitz, Tomer D. Ullman, Alison Gopnik, Joshua B. Tenenbaum:
Sticking to the Evidence? A computational and behavioral case study of micro-theory change in the domain of magnetism. ICDL-EPIROB 2012: 1-6 - 2011
- [c2]Tomer D. Ullman, Noah D. Goodman, Josh Tenenbaum:
Forward Physics: How people learn and generalize novel dynamical models. CogSci 2011
2000 – 2009
- 2009
- [c1]Tomer D. Ullman, Chris L. Baker, Owen Macindoe, Owain Evans, Noah D. Goodman, Joshua B. Tenenbaum:
Help or Hinder: Bayesian Models of Social Goal Inference. NIPS 2009: 1874-1882
Coauthor Index
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