## Papers

(* indicates equal contribution)

**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, T.L. Griffiths

**Nature Human Behavior**

**Conditional and modal reasoning in large language models**

W.H. Holliday, M. Mandelkern, and C.E. Zhang

**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

**arXiv (Presented at CogSci 2024)**

**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**

T.X. Olausson*, A. Gu*, B. Lipkin*, C.E. Zhang*, 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**

**When do introspection axioms matter for multi-agent epistemic reasoning?**

Y. Ding, W.H. Holliday, and C. Zhang

**TARK 2019**