Lionel Wong

According to our database, Lionel Wong authored at least 15 papers between 2023 and 2024.

Collaborative distances:

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

2024

Understanding Epistemic Language with a Bayesian Theory of Mind.

Lance Ying, Tan Zhi-Xuan, Lionel Wong, Vikash Mansinghka, 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, Cedegao E. Zhang, Tan Zhi-Xuan, Mark K. Ho, Vikash Mansinghka, Adrian Weller, Joshua B. Tenenbaum, Thomas L. Griffiths

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

Finding structure in logographic writing with library learning.

Guangyuan Jiang, Matthias Hofer, Jiayuan Mao, Lionel Wong, Joshua B. Tenenbaum, Roger P. Levy

CoRR, 2024

Grounding Language about Belief in a Bayesian Theory-of-Mind.

Lance Ying, Tan Zhi-Xuan, Lionel Wong, Vikash Mansinghka, Joshua B. Tenenbaum

CoRR, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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., January, 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

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

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

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, Adrian Weller, Mateja Jamnik

CoRR, 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

How does the mind discover useful abstractions?

Marcelo Gomes Mattar, Judith E. Fan, Wai Keen Vong, Lionel Wong

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

Evaluating statistical language models as pragmatic reasoners.

Benjamin Lipkin, Lionel Wong, Gabriel Grand, Josh Tenenbaum

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