Zhu Jian-Qiao
I am a postdoc in the Computational Cognitive Science Lab at Princeton University, USA, where I work with Tom Griffiths. I completed my PhD in Psychology at the University of Warwick, UK.
I am interested in understanding the rational principles of human cognition and machine behavior, particularly in relation to judgment and decision-making processes.
Google Scholar / Twitter / Email: jz5204 [at] princeton [dot] edu
Preprints
Elga, A., Zhu, J. Q., & Griffiths, T. L. (submitted). People Make Suboptimal Decisions about Existential Risks.
Zhang, L., McCoy, R. T., Sumers, T., Zhu, J. Q., & Griffiths, T. L. (submitted). Deep de Finetti: Recovering Topic Distributions from Large Language Models. arXiv.
Griffiths, T. L., Zhu, J. Q., Grant, E., & McCoy, R. T. (submitted). Bayes in the age of intelligent machines. arXiv.
Sanborn, A. N., Zhu, J. Q., Spicer, J., Leon-Villagra, P., Castillo, L., Falben, J. K., Li, Y- X, Tee, A., & Chater, N. (submitted). Noise in Cognition: Bug or Feature? PsyArXiv.
Zhu, J. Q., Spicer, J., Sanborn, A. N., & Chater, N. (submitted). Cognitive Variability Matches Speculative Price Dynamics. PsyArXiv.
Publications
2024
Spicer, J., Zhu, J. Q., Chater, N., & Sanborn, A. N. (2024). How do people predict a random walk? Lessons for models of cognition. Psychological Review.
Zhu, J. Q., & Griffiths, T. L. (2024). Incoherent Probability Judgments in Large Language Models. Proceedings of the 46th Annual Conference of the Cognitive Science Society. Oral
Zhu, J. Q., Yan, H., & Griffiths, T. L. (2024). Recovering Mental Representations from Large Language Models with Markov Chain Monte Carlo. Proceedings of the 46th Annual Conference of the Cognitive Science Society. Oral
Zhu, J. Q., Chater, N., Leon-Villagra, P., Spicer, J., Sundh, J., & Sanborn, A. N. (2024). An Introduction to Psychologically Plausible Sampling Schemes for Approximating Bayesian Inference. In K. Fielder, P. Juslin, & J. Denrell (Eds.), Sampling in Judgment and Decision Making, Cambridge University Press, UK.
Sundh, J., Sanborn, A. N., Zhu, J. Q., Spicer, J., Leon-Villagra, P., & Chater, N. (2024). Approximating Bayesian Inference through Internal Sampling. In K. Fielder, P. Juslin, & J. Denrell (Eds.), Sampling in Judgment and Decision Making, Cambridge University Press, UK.
2023
Zhu, J. Q., Sundh, J., Spicer, J., Chater, N., & Sanborn, A. N. (2023). The Autocorrelated Bayesian Sampler: A Rational Process for Probability Judgments, Estimates, Confidence Intervals, Choices, Confidence Judgments, and Response Times. Psychological Review.
Sundh, J., Zhu, J. Q., Chater, N., & Sanborn A. N. (2023). A Unified Explanation of Variability and Bias in Human Probability Judgments: How Computational Noise Explains the Mean-Variance Signature. Journal of Experimental Psychology: General.
Xia. F., Zhu, J. Q., & Griffiths, T. L. (2023). Comparing Human Predictions from Expert Advice to On-line Optimization Algorithms. Proceedings of the 45th Annual Conference of the Cognitive Science Society.
Zhu, J. Q., Sanborn, A. N., Chater, N., & Griffiths, T. L. (2023). Computation-Limited Bayesian Updating. Proceedings of the 45th Annual Conference of the Cognitive Science Society.
Newall, P. W. S. & Zhu, J. Q. (2023). Skilled Poker Players Provide More Accurate Responses than Amateur Poker Players to the Gambling Fallacies Measure. Journal of Gambling Issues.
2022
Zhu, J. Q., Leon-Villagra, P., Chater, N., & Sanborn, A. N. (2022). Understanding the Structure of Cognitive Noise. PLoS Computational Biology.
Spicer, J., Zhu, J. Q., Chater, N., & Sanborn, A. N. (2022). Perceptual and Cognitive Judgments Show Both Anchoring and Repulsion. Psychological Science.
Zhu, J. Q., Newall, P. W. S., Sundh, J., Chater, N., & Sanborn, A. N. (2022). Clarifying the Relationship between Accuracy and Coherence in Probability Judgments. Cognition.
2021
Sanborn, A. N., Zhu, J. Q., Spicer, J., Sundh, J., Leon-Villagra, P., & Chater, N. (2021). Sampling as the human approximation to probabilistic inference. In S. Muggleton & N. Chater, (Eds.), Human-like Machine Intelligence, Oxford University Press, UK.
2020
Chater, N., Zhu, J. Q., Spicer, J., Sundh, J., Leon-Villagra, P., & Sanborn, A. N. (2020). Probabilistic Biases Meet the Bayesian Brain. Current Directions in Psychological Science.
Zhu, J. Q., Sanborn, A. N., & Chater, N. (2020). The Bayesian Sampler: Generic Bayesian Inference Causes Incoherence in Human Probability Judgments. Psychological Review.
2019
Sanborn, A. N., Zhu, J. Q., Spicer, J., & Chater, N. (2019). Sampling as a Resource-rational Constraints. Behavioural and Brain Science.
Cabrero, J. A., Zhu, J. Q., & Ludvig, E. A. (2019). Costly Curiosity: People Pay a Price to Resolve an Uncertain Gamble Early. Behavioral Processes.
Zhu, J. Q., Sanborn, A. N., & Chater, N. (2019). Why Decisions Bias Perception: An Amortised Sequential Sampling Account. Proceedings of the 41st Annual Cognitive Science Society.
2018 and before
Zhu, J. Q., Sanborn, A. N., & Chater, N. (2018). Mental Sampling in Multimodal Representations. Advances in Neural Information Processing Systems 31.
Zhu, J. Q., Xiang, W., & Ludvig, E. A. (2017). Information Seeking as Chasing Anticipated Prediction Errors. Proceedings of the 39th Annual Cognitive Science Society.
Last update: Apr 2024