Papers
(* indicates equal contribution; 𝛼 indicates alphabetical author list)
Code-enabled language models can outperform reasoning models on diverse tasks
C.E. Zhang, C. Colas, G. Poesia, J.B. Tenenbaum, J. Andreas
arXiv preprint
People use fast, flat goal-directed simulation to reason about novel problems
K.M. Collins*, C.E. Zhang*, L. Wong*, M. Barba da Costa*, G. Todd*, A. Weller, S.J. Cheyette, T.L. Griffiths, J.B. Tenenbaum
arXiv preprint
Evaluating language models' evaluations of games
K.M. Collins, C.E. Zhang, G. Todd, L. Ying, M. Barba da Costa, R. Liu, P. Sharma, A. Weller, I. Kuperwajs, L. Wong, J.B. Tenenbaum, T.L. Griffiths
arXiv preprint
On the same wavelength? Evaluating pragmatic reasoning in language models across broad concepts
L. Qiu*, C.E. Zhang*, J.B. Tenenbaum, Y. Kim, and R.P. Levy
EMNLP 2025
Language-informed synthesis of rational agent models for grounded Theory-of-Mind reasoning on-the-fly
L. Ying, R. Truong, K.M. Collins, C.E. Zhang, M. Wei, T. Brooke-Wilson, T. Zhi-Xuan, L. Wong, and J.B. Tenenbaum,
EMNLP 2025 Findings
Modeling open-world cognition as on-demand synthesis of probabilistic models
L. Wong*, K.M. Collins*, L. Ying, C.E. Zhang, A. Weller, T. Gersternberg, T. O'Donnell, A.K. Lew, J.D. Andreas, J.B. Tenenbaum, and T. Brooke-Wilson
CogSci 2025 (Talk)
Scaling up the think-aloud method
D. Wurgaft*, B. Prystawski*, K. Gandhi, C.E. Zhang, J.B. Tenenbaum, and N.D. Goodman
CogSci 2025 (Talk)
Building machines that learn and think with people
K.M. Collins*, I. Sucholutsky*, U. Bhatt*, K. Chandra*, L. Wong*, M. Lee, C.E. Zhang, T. Zhi-Xuan, M. Ho, V. Mansinghka, A. Weller, J.B. Tenenbaum, and T.L. Griffiths
Nature Human Behavior
Conditional and modal reasoning in large language models
W.H. Holliday, M. Mandelkern, and C.E. Zhang𝛼
EMNLP 2024
People use fast, goal-directed simulations to reason about novel games
C.E. Zhang*, K.M. Collins*, L. Wong*, A. Weller, and J.B. Tenenbaum
CogSci 2024 (Talk)
AI for mathematics: A cognitive science perspective
C.E. Zhang*, K.M. Collins*, A. Weller, and J.B. Tenenbaum
MATH-AI Workshop at NeurIPS 2023
LINC: A neurosymbolic approach for logical reasoning by combining language models with first-order logic provers
C.E. Zhang*, T.X. Olausson*, A. Gu*, B. Lipkin*, A. Solar-Lezama, J.B. Tenenbaum, and R. Levy
EMNLP 2023 (Outstanding paper award)
The neuro-symbolic inverse planning engine (NIPE): modeling probabilistic social inferences from linguistic inputs
L. Ying, K.M. Collins, M. Wei, C.E. Zhang, T. Zhi-Xuan, A. Weller, J.B. Tenenbaum, and L. Wong
ToM Workshop at ICML 2023
Towards a model of confidence judgements in concept learning
T.E. Mills*, T. Chen*, C.E. Zhang*, and J.B. Tenenbaum
CogSci 2023
Grounded physical language understanding with probabilistic programs and simulated worlds
C.E. Zhang, L. Wong, G. Grand, and J.B. Tenenbaum
CogSci 2023
Does Amy know Ben knows you know your cards? A computational model of higher-order epistemic reasoning
C. Zhang*, H. Ham*, and W.H. Holliday
CogSci 2021
A model of temporal connective acquisition
M. Gorenstein*, C. Zhang*, and S.T. Piantadosi
CogSci 2020 (Talk)
When do introspection axioms matter for multi-agent epistemic reasoning?
Y. Ding, W.H. Holliday, and C. Zhang𝛼
TARK 2019