Evaluating statistical language models as pragmatic reasoners. - Benjamin Lipkin; Lionel Wong; Gabriel Grand; Josh Tenenbaum 001 (CogSci, 2023)

How does the mind discover useful abstractions? - Marcelo Gomes Mattar; Judith E. Fan; Wai Keen Vong; Lionel Wong (CogSci, 2023)

Grounded physical language understanding with probabilistic programs and simulated worlds. - Cedegao Zhang; Lionel Wong; Gabriel Grand; Josh Tenenbaum 001 (CogSci, 2023)

Evaluating Language Models for Mathematics through Interactions. - Katherine M. Collins; Albert Q. Jiang; Simon Frieder; Lionel Wong; Miri Zilka; Umang Bhatt; Thomas Lukasiewicz; Yuhuai Wu; Joshua B. Tenenbaum; William Hart; Timothy Gowers; Wenda Li; et al. (CoRR, 2023)

From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought. - Lionel Wong; Gabriel Grand; Alexander K. Lew; Noah D. Goodman; Vikash K. Mansinghka; Jacob Andreas; 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)

Learning adaptive planning representations with natural language guidance. - Lionel Wong; Jiayuan Mao; Pratyusha Sharma; Zachary S. Siegel; Jiahai Feng; Noa Korneev; Joshua B. Tenenbaum; Jacob Andreas (CoRR, 2023)

Top-Down Synthesis for Library Learning. - Matthew Bowers; Theo X. Olausson; Lionel Wong; Gabriel Grand; Joshua B. Tenenbaum; Kevin Ellis; Armando Solar-Lezama (Proc. ACM Program. Lang., 2023)

LILO: Learning Interpretable Libraries by Compressing and Documenting Code. - Gabriel Grand; Lionel Wong; Matthew Bowers; Theo X. Olausson; Muxin Liu; Joshua B. Tenenbaum; Jacob Andreas (ICLR, 2024)

Learning Grounded Action Abstractions from Language. - Lionel Wong; Jiayuan Mao; Pratyusha Sharma; Zachary S. Siegel; Jiahai Feng; Noa Korneev; Joshua B. Tenenbaum; Jacob Andreas (ICLR, 2024)

Grounding Language about Belief in a Bayesian Theory-of-Mind. - Lance Ying; Tan Zhi-Xuan; Lionel Wong; Vikash Mansinghka 001; Joshua B. Tenenbaum (CoRR, 2024)

Finding structure in logographic writing with library learning. - Guangyuan Jiang; Matthias Hofer 002; Jiayuan Mao; Lionel Wong; Joshua B. Tenenbaum; Roger P. Levy (CoRR, 2024)

People use fast, goal-directed simulation to reason about novel games. - Cedegao E. Zhang; Katherine M. Collins; Lionel Wong; Adrian Weller; Joshua B. Tenenbaum (CoRR, 2024)

Building Machines that Learn and Think with People. - Katherine M. Collins; Ilia Sucholutsky; Umang Bhatt; Kartik Chandra; Lionel Wong; Mina Lee 002; Cedegao E. Zhang; Tan Zhi-Xuan; Mark K. Ho; Vikash Mansinghka 001; Adrian Weller; Joshua B. Tenenbaum; et al. (CoRR, 2024)

Understanding Epistemic Language with a Bayesian Theory of Mind. - Lance Ying; Tan Zhi-Xuan; Lionel Wong; Vikash Mansinghka 001; Joshua B. Tenenbaum (CoRR, 2024)

Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind. - Lance Ying; Tan Zhi-Xuan; Lionel Wong; Vikash Mansinghka 001; Joshua B. Tenenbaum (Trans. Assoc. Comput. Linguistics, 2025)

Retrieval-augmented systems can be dangerous medical communicators. - Lionel Wong; Ayman Ali; Raymond Xiong; Shannon Zejiang Shen; Yoon Kim; Monica Agrawal (CoRR, 2025)

On Benchmarking Human-Like Intelligence in Machines. - Lance Ying; Katherine M. Collins; Lionel Wong; Ilia Sucholutsky; Ryan Liu 001; Adrian Weller; Tianmin Shu; Thomas L. Griffiths 001; Joshua B. Tenenbaum (CoRR, 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 (CoRR, 2025)

Resource Rational Contractualism Should Guide AI Alignment. - Sydney Levine; Matija Franklin; Tan Zhi-Xuan; Secil Yanik Guyot; Lionel Wong; Daniel Kilov; Yejin Choi 001; Joshua B. Tenenbaum; Noah D. Goodman; Seth Lazar; Iason Gabriel (CoRR, 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; Joshua B. Tenenbaum; Tyler Brooke-Wilson (CoRR, 2025)