1. Zhi-Xuan, T.†, Carroll, M., Franklin, M., & Ashton, H. (2025). Beyond Preferences in AI Alignment. Phil. Studies.
2. Ying, L., Zhi-Xuan, T., Wong, L., Mansinghka, V., & Tenenbaum, J. B. (2025). Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind. Transactions of the Association for Computational Linguistics, 13, 613-637.
3. Collins, K.M., Sucholutsky, I., Bhatt, U., Chandra, K., Wong, L., Lee, M., Zhang, C., Zhi-Xuan, T., Ho, M., Mansinghka, V., Weller, A., Tenenbaum, J.B., & Griffiths, T.L. (2024). Building Machines that Learn and Think with People. Nature Hum. Behav.
4. Zhi-Xuan, T.*†, Ying, L.*, Mansinghka, V., & Tenenbaum, J. B. (2024). Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning. The 23rd International Conference on Autonomous Agents and Multiagent Systems.
5. Oldenburg, N., & Zhi-Xuan, T.‡ (2024). Learning and Sustaining Shared Normative Systems via Bayesian Rule Induction in Markov Games. The 23rd International Conference on Autonomous Agents and Multiagent Systems.
6. Zhi-Xuan, T.†, Kang, G., Mansinghka, V., & Tenenbaum, J. (2024). Infinite Ends from Finite Samples Open Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals. Annual Meeting of the Cognitive Science Society, 46.
7. Ying, L.*, Zhi-Xuan, T..*, Wong, L., Mansinghka, V., & Tenenbaum, J. B. (2024). Grounding Language about Belief in Theory-of-Mind. Annual Meeting of the Cognitive Science Society, 46.
8. Lew, A. K., Matheos, G., Zhi-Xuan, T., Ghavamizadeh, M., Gothoskar, N., Russell, S., & Mansinghka, V. (2023). SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals Int’l Conference on Artificial Intelligence & Statistics.
9. Kwon, J., Zhi-Xuan, T., Tenenbaum, J., & Levine, S. (2023). When it is not out of line to get out of line: The Role of Universalisation and Outcome-based Reasoning in Rule-breaking Judgments. Annual Meeting of the Cognitive Science Society, 45.
10. Alanqary, A.*, Lin, G. Z.*, Le, J.*, Zhi-Xuan, T.*†, Mansinghka, V., & Tenenbaum, J. B. (2021). Modelling the Mistakes of Boundedly Rational Agents Within a Bayesian Theory of Mind. Annual Meeting of the Cognitive Science Society, 43.
11. Zhi-Xuan, T.†, Mann, J., Silver, T., Tenenbaum, J. B., & Mansinghka, V. (2020). Online Bayesian Goal Inference for Boundedly Rational Planning Agents. Advances in Neural Information Processing Systems, 33, 19238-19250.
12. Zhi-Xuan, T., Soh, H., & Ong, D. C. (2020). Factorised Inference in Deep Markov Models for Incomplete Time Series. Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence.