Tan Zhi-Xuan

According to our database, Tan Zhi-Xuan authored at least 18 papers between 2020 and 2024.

Collaborative distances:

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

2024

Beyond Preferences in AI Alignment.

Tan Zhi-Xuan, Micah Carroll, Matija Franklin, Hal Ashton

CoRR, 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

Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals.

Tan Zhi-Xuan, Gloria Kang, Vikash Mansinghka, Joshua B. Tenenbaum

CoRR, 2024

Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems.

David Dalrymple, Joar Skalse, Yoshua Bengio, Stuart Russell, Max Tegmark, Sanjit Seshia, Steve Omohundro, Christian Szegedy, Ben Goldhaber, Nora Ammann, Alessandro Abate, Joe Halpern, Clark W. Barrett, Ding Zhao, Tan Zhi-Xuan, Jeannette Wing, Joshua B. Tenenbaum

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

Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning.

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

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Learning and Sustaining Shared Normative Systems via Bayesian Rule Induction in Markov Games.

Ninell Oldenburg, Tan Zhi-Xuan

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Inferring the Goals of Communicating Agents from Actions and Instructions.

Lance Ying, Tan Zhi-Xuan, Vikash Mansinghka, 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

Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs.

Alexander K. Lew, Tan Zhi-Xuan, Gabriel Grand, Vikash K. Mansinghka

CoRR, 2023

Language Models as Informative Goal Priors in a Bayesian Theory of Mind.

Tan Zhi-Xuan, Paul Stefan Lunis, Nathalie Fernandez Echeverri, Vikash Mansinghka, Josh Tenenbaum

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

When it's not out of line to get out of line: Principles of universalizability, welfare, and harm.

Joseph Kwon, Tan Zhi-Xuan, Josh Tenenbaum, Sydney Levine

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

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals.

Alexander K. Lew, George Matheos, Tan Zhi-Xuan, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, Vikash K. Mansinghka

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Abstract Interpretation for Generalized Heuristic Search in Model-Based Planning.

Tan Zhi-Xuan, Joshua B. Tenenbaum, Vikash K. Mansinghka

CoRR, 2022

Solving the Baby Intuitions Benchmark with a Hierarchically Bayesian Theory of Mind.

Tan Zhi-Xuan, Nishad Gothoskar, Falk Pollok, Dan Gutfreund, Joshua B. Tenenbaum, Vikash K. Mansinghka

CoRR, 2022

2021

Modeling the Mistakes of Boundedly Rational Agents Within a Bayesian Theory of Mind.

Arwa Alanqary, Gloria Z. Lin, Joie Le, Tan Zhi-Xuan, Vikash Mansinghka, Josh Tenenbaum

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

2020

Online Bayesian Goal Inference for Boundedly Rational Planning Agents.

Tan Zhi-Xuan, Jordyn L. Mann, Tom Silver, Josh Tenenbaum, Vikash Mansinghka

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020