Cedegao E. Zhang

According to our database, Cedegao E. Zhang authored at least 21 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Cognitive Models and AI Algorithms Provide Templates for Designing Language Agents.

Ryan Liu, Dilip Arumugam, Cedegao E. Zhang, Sean Escola, Xaq Pitkow, Thomas L. Griffiths

CoRR, February, 2026

2025

A Matter of Interest: Understanding Interestingness of Math Problems in Humans and Language Models.

Shubhra Mishra, Yuka Machino, Gabriel Poesia, Albert Q. Jiang, Joy Hsu, Adrian Weller, Challenger Mishra, David Broman, Joshua B. Tenenbaum, Mateja Jamnik, Cedegao E. Zhang, Katherine M. Collins

CoRR, November, 2025

Code-enabled language models can outperform reasoning models on diverse tasks.

Cedegao E. Zhang, Cédric Colas, Gabriel Poesia, Joshua B. Tenenbaum, Jacob Andreas

CoRR, October, 2025

People use fast, flat goal-directed simulation to reason about novel problems.

Katherine M. Collins, Cedegao E. Zhang, Lionel Wong, Mauricio Barba da Costa, Graham Todd, Adrian Weller, Samuel J. Cheyette, Thomas L. Griffiths, Joshua B. Tenenbaum

CoRR, October, 2025

Evaluating Language Models' Evaluations of Games.

Katherine M. Collins, Cedegao E. Zhang, Graham Todd, Lance Ying, Mauricio Barba da Costa, Ryan Liu, Prafull Sharma, Adrian Weller, Ionatan Kuperwajs, Lionel Wong, Joshua B. Tenenbaum, Thomas L. Griffiths

CoRR, October, 2025

Language-Informed Synthesis of Rational Agent Models for Grounded Theory-of-Mind Reasoning On-the-fly.

Lance Ying, Ryan Truong, Katherine M. Collins, Cedegao E. Zhang, Megan Wei, Tyler Brooke-Wilson, Tan Zhi-Xuan, Lionel Wong, Joshua B. Tenenbaum

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

On the Same Wavelength? Evaluating Pragmatic Reasoning in Language Models across Broad Concepts.

Linlu Qiu, Cedegao E. Zhang, Joshua B. Tenenbaum, Yoon Kim, Roger P. Levy

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Scaling up the think-aloud method.

Daniel Wurgaft, Ben Prystawski, Kanishk Gandhi, Cedegao E. Zhang, Joshua B. Tenenbaum, Noah D. Goodman

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models.

Lionel Wong, Katherine M. Collins, Lance Ying, Cedegao E. Zhang, Adrian Weller, Tobias Gerstenberg, Timothy O'Donnell, Alexander K. Lew, Jacob Andreas, Tyler Brooke-Wilson, Joshua B. Tenenbaum

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

Generation and Evaluation in the Human Invention Process through the Lens of Game Design.

Katherine M. Collins, Graham Todd, Cedegao E. Zhang, Adrian Weller, Julian Togelius, Junyi Chu, Lionel Wong, Tom Griffiths, Joshua B. Tenenbaum

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

2024

Building Machines that Learn and Think with People.

Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E. Zhang, Tan Zhi-Xuan, Mark K. Ho, Vikash Mansinghka, Adrian Weller, Joshua B. Tenenbaum, Thomas L. Griffiths

CoRR, 2024

Conditional and Modal Reasoning in Large Language Models.

Wesley H. Holliday, Matthew Mandelkern, Cedegao Zhang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

People use fast, goal-directed simulation to reason about novel games.

Cedegao E. Zhang, Katherine M. Collins, Lionel Wong, Adrian Weller, Josh Tenenbaum

Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

2023

AI for Mathematics: A Cognitive Science Perspective.

Cedegao E. Zhang, Katherine M. Collins, Adrian Weller, Joshua B. Tenenbaum

CoRR, 2023

The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs.

Lance Ying, Katherine M. Collins, Megan Wei, Cedegao E. Zhang, Tan Zhi-Xuan, Adrian Weller, Joshua B. Tenenbaum, Lionel Wong

CoRR, 2023

LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers.

Theo Olausson, Alex Gu, Benjamin Lipkin, Cedegao E. Zhang, Armando Solar-Lezama, Joshua B. Tenenbaum, Roger Levy

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Grounded physical language understanding with probabilistic programs and simulated worlds.

Cedegao Zhang, Lionel Wong, Gabriel Grand, Josh Tenenbaum

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

Towards a model of confidence judgements in concept learning.

Tracey Mills, Cedegao Zhang, Tony Chen, Josh Tenenbaum

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

2021

Does Amy Know Ben Knows You Know Your Cards? A Computational Model of Higher-Order Epistemic Reasoning.

Cedegao Zhang, Ham Huang, Wesley H. Holliday

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

A Model of Temporal Connective Acquisition.

Mark Gorenstein, Cedegao Zhang, Steven T. Piantadosi

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

2019

When Do Introspection Axioms Matter for Multi-Agent Epistemic Reasoning?

Yifeng Ding, Wesley H. Holliday, Cedegao Zhang

Proceedings of the Proceedings Seventeenth Conference on Theoretical Aspects of Rationality and Knowledge, 2019