Online Bayesian Goal Inference for Boundedly Rational Planning Agents. - Tan Zhi-Xuan; Jordyn L. Mann; Tom Silver; Josh Tenenbaum 001; Vikash Mansinghka 001 (NeurIPS, 2020)

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 001; Josh Tenenbaum 001 (CogSci, 2021)

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)

Abstract Interpretation for Generalized Heuristic Search in Model-Based Planning. - Tan Zhi-Xuan; Joshua B. Tenenbaum; Vikash K. Mansinghka (CoRR, 2022)

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals. - Alexander K. Lew; George Matheos; Tan Zhi-Xuan; Matin Ghavamizadeh; Nishad Gothoskar; Stuart Russell 001; Vikash K. Mansinghka (AISTATS, 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 001; Sydney Levine (CogSci, 2023)

Language Models as Informative Goal Priors in a Bayesian Theory of Mind. - Tan Zhi-Xuan; Paul Stefan Lunis; Nathalie Fernandez Echeverri; Vikash Mansinghka 001; Josh Tenenbaum 001 (CogSci, 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)

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)

Inferring the Goals of Communicating Agents from Actions and Instructions. - Lance Ying; Tan Zhi-Xuan; Vikash Mansinghka 001; Joshua B. Tenenbaum (CoRR, 2023)

Learning and Sustaining Shared Normative Systems via Bayesian Rule Induction in Markov Games. - Ninell Oldenburg; Tan Zhi-Xuan (AAMAS, 2024)

Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning. - Tan Zhi-Xuan; Lance Ying; Vikash Mansinghka 001; Joshua B. Tenenbaum (AAMAS, 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)

Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. - David Dalrymple; Joar Skalse; Yoshua Bengio; Stuart Russell 001; Max Tegmark; Sanjit Seshia; Steve Omohundro; Christian Szegedy; Ben Goldhaber; Nora Ammann; Alessandro Abate; Joe Halpern; et al. (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 001; 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)

Beyond Preferences in AI Alignment. - Tan Zhi-Xuan; Micah Carroll; Matija Franklin; Hal Ashton (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)

Resource-Rational Virtual Bargaining for Moral Judgment: Toward a Probabilistic Cognitive Model. - Diego Trujillo; Mindy Zhang; Tan Zhi-Xuan; Joshua B. Tenenbaum; Sydney Levine (Top. Cogn. Sci., 2025)

Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models. - Hyunwoo Kim 002; Melanie Sclar; Tan Zhi-Xuan; Lance Ying; Sydney Levine; Yang Liu; Joshua B. Tenenbaum; Yejin Choi 001 (CoRR, 2025)

Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality. - Lance Ying; Almog Hillel; Ryan Truong; Vikash K. Mansinghka; Joshua B. Tenenbaum; Tan Zhi-Xuan (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)