Charles Kemp

I work at the School of Psychological Sciences at the University of Melbourne.

 
Email:  

Research Interests

My research focuses on computational models of learning, reasoning and communication. Much of my recent work aims to analyze linguistic and cultural variation, and an earlier line of work focused on categorization, generalization, causal reasoning, and relational learning. My approach draws on tools from information theory, natural language processing, AI and statistics and I am especially interested in the analysis of large, naturally occurring data sets (e.g. dictionaries and linguistic corpora).

Selected Papers

Lim, Z. W., Stuart, H., De Deyne, S., Regier, T., Vylomova, E., Cohn, T. & Kemp, C. (2024). A computational approach to identifying cultural keywords across languages. Cognitive Science Preprint Code and Data.  Compare usage and association frequencies across languages using the Keyword Explorer.

Han, S. J., Kelly, P., Winters, J. & Kemp, C. (2022). Simplification is not dominant in the evolution of Chinese characters. Open Mind PreprintCodeConversation piece.  Coverage on Language Log and SBS Radio.   Explore how individual characters have changed in complexity here.

Kemp, C., Hamacher, D. W., Little, D. R. & Cropper, S. J. (2022). Perceptual grouping explains similarities in constellations across cultures. Psychological Science Preprint SI MovieCode and data.  Coverage in Psychology Today, APS Research News , Cosmos, Discover Magazine, and Popular Science.  Interviews with Under the Cortex and The Naked Scientists.  Related pieces in Psyche, The Conversation and Nature Astronomy.

Mollica, F., Bacon, G., Zaslavsky, N., Xu, Y., Regier, T. & Kemp, C. (2021). The forms and meanings of grammatical markers support efficient communication. Proceedings of the National Academy of Sciences.   Preprint Supplementary information Code and data TICS Spotlight by Shane Steinert-Threlkeld

Zaslavsky, N., Kemp, C., Regier, T. & Tishby, N. (2018). Efficient compression in color naming and its evolution. Proceedings of the National Academy of Sciences. Supporting information Movie

Kemp C., Xu Y. & Regier, T. (2018). Semantic typology and efficient communication. Annual Review of Linguistics. 4, 109-128.

Jern, A., Lucas, C. G., & Kemp, C. (2017). People learn other people's preferences through inverse decision-making. Cognition. 168, 46-64. Code, data, and materials.

Navarro, D. J. & Kemp C. (2017). None of the above: A Bayesian account of the detection of novel categories. Psychological Review. 124(5), 643-677.

Regier, T., Carstensen, A. & Kemp C. (2016). Languages support efficient communication about the environment: Words for snow revisited. PLOS ONE. 11(4). Github repository.

Lucas, C. G. & Kemp C. (2015). An improved probabilistic account of counterfactual reasoning. Psychological Review. 122(4), 700-734.

Jern, A., Chang, K. K. & Kemp C. (2014). Belief polarization is not always irrational. Psychological Review. 121(2), 206-224.

Kemp, C. & Jern, A. (2014). A taxonomy of inductive problems. Psychonomic Bulletin & Review. 21(1), 23-46.

Jern, A. & Kemp, C. (2013). A probabilistic account of exemplar and category generation. Cognitive Psychology. 66(1), 85-125.

Kemp, C. (2012). Exploring the conceptual universe. Psychological Review. 119(4), 685-722. Code and data.

Kemp, C., & Regier, T. (2012). Kinship categories across languages reflect general communicative principles. Science. 336(6084), 1049-1054.   Supplementary material Commentary by S. C. Levinson.  Science podcast Project page FAQ Video

Kemp, C., Shafto, P., & Tenenbaum, J. B. (2012) An integrated account of generalization across objects and features. Cognitive Psychology. 64 (1-2), 35-73.

Tenenbaum, J. B., Kemp, C., Griffiths, T. L. & Goodman, N. D. (2011). How to grow a mind: statistics, structure and abstraction. Science. 331(6022), 1279-1285.

Kemp, C., Tenenbaum, J. B., Niyogi, S. & Griffiths, T. L. (2010) A probabilistic model of theory formation. Cognition. 114(2), 165-196. Code and data sets.

Kemp, C., & Tenenbaum, J. B. (2009). Structured statistical models of inductive reasoning. Psychological Review. 116(1), 20-58. Code and data sets.

Kemp, C., & Tenenbaum, J. B. (2008). The discovery of structural form. Proceedings of the National Academy of Sciences. 105(31), 10687-10692.   Supporting information Commentary by K. J. Holyoak.  Code and data sets.

Kemp, C., Perfors, A. & Tenenbaum, J. B. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.

Other Papers

2024

Warburton, K., Kemp, C., Xu, Y. & Frermann, L. (2024). Quantifying bias in hierarchical category systems. Open Mind

Kelly, B., Kemp, C., Little, D. R., Hamacher, D. & Cropper, S. (2024). Visual perception principles in constellation creation. Topics in Cognitive Science

Zhang, C., Kemp, C. & Lipovetzky, N. (2024). Human Goal Recognition as Bayesian Inference: Investigating the Impact of Actions, Timing, and Goal Solvability. Proceedings of the 2024 International Conference on Autonomous Agents and Multiagent Systems

2023

Han, S. J., Ransom, K. J., Perfors, A. & Kemp, C. (2023). Inductive reasoning in humans and large language models. Cognitive Systems Research PreprintCode and data.

Kelly, B., Kemp, C., Little, D. R., Hamacher, D. & Cropper, S. Visual perception principles in constellation creation. Proceedings of the 45th Annual Meeting of the Cognitive Science Society. Disciplinary Diversity and Integration Award

Xu, W., Cropper, S. & Kemp, C. (2023). A Bayesian account of two visual illusions involving lighthouse beams. Proceedings of the 45th Annual Meeting of the Cognitive Science Society.

Warburton, K., Kemp, C., Xu, Y. & Frermann, L. (2023). Quantifying bias in library classification systems. Proceedings of the 45th Annual Meeting of the Cognitive Science Society.

Xu, A., Kemp, C., Frermann, L. & Xu, Y. (2023). Predicting strategy choice in word formation: A case study of reuse and compounding. Proceedings of the 45th Annual Meeting of the Cognitive Science Society.

Gualdoni, E., Kemp, C., Xu, Y. & Boleda, G. (2023). Quantifying informativeness of names in visual space. Proceedings of the 45th Annual Meeting of the Cognitive Science Society.

Zhang, C., Kemp, C., & Lipovetzky, N. (2023). Comparing AI planning systems with humans on the Tower of London task. Proceedings of the 45th Annual Meeting of the Cognitive Science Society.

Lim, Z. W., Cohn, T., Kemp, C., & Vylomova, E. (2023). Predicting human translation difficulty using automatic word alignment. Findings of the Association for Computational Linguistics: ACL 2023.

Mansfield, J., & Kemp, C. (2023). The emergence of grammatical structure from interpredictability. In A Festschrift for Jane Simpson

Zhang, C., Kemp, C. & Lipovetzky, N. (2023). Goal recognition with timing information. Proceedings of the International Conference on Automated Planning and Scheduling.  

2022

Kemp, C., Hamacher, D. W., Little, D. R. & Cropper, S. J. (2022). Comparing constellations across cultures. Nature Astronomy Preprint

Zaslavsky, N., Garvin, K., Kemp, C., Tishby, N. & Regier, T. (2022). The evolution of color naming reflects pressure for efficiency: Evidence from the recent past . Journal of Language Evolution Preprint

Han, S. J., Ransom, K. J., Perfors, A. & Kemp, C. (2022). Human-like property induction is a challenge for large language models. Proceedings of the 44th Annual Meeting of the Cognitive Science Society.   Github repository. After submitting the camera-ready version we discovered a bug in the code that generated results for Non-monotonicity (General) in Figure 1. A corrected version of the figure is here.

Xu, A., Kemp, C., Frermann, L. & Xu, Y. (2022). Word formation supports efficient communication: The case of compounds. Proceedings of the 44th Annual Meeting of the Cognitive Science Society.

2021

Fermo, A. & Kemp, C. (2021). Temporal continuity and the judgment of actual causation. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society.   Github repository.

2020

Habibi, A. A., Kemp, C. & Xu, Y. (2020). Chaining and the growth of linguistic categories. Cognition.   Github repository.

Abbott, J. T. & Kemp, C. (2020). Birds and Words: Exploring environmental influences on folk categorization. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society.   Github repository.

Mollica, F., Bacon, G., Xu, Y., Regier, T. & Kemp, C. (2020). Grammatical marking and the tradeoff between code length and informativeness. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society.   OSF project .

Mollica, F. & Kemp, C. (2020). An efficient communication analysis of morpho-syntactic grammatical features. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society.

2019

Kemp, C., Gaby, A. & Regier, T. (2019). Season naming and the local environment. Proceedings of the 41st Annual Meeting of the Cognitive Science Society.

Zaslavsky, N., Regier, T., Tishby, N. & Kemp, C. (2019). Semantic categories of artifacts and animals reflect efficient coding. Proceedings of the 41st Annual Meeting of the Cognitive Science Society.

Zaslavsky, N., Kemp, C., Tishby, N. & Regier, T. (2019). Communicative need in color naming. Cognitive Neuropsychology

2018

Rothe, A., Deverett, B., Mayrhofer, R. & Kemp, C. (2018). Successful structure learning from observational data. Cognition. 179, 266-297.   Github repository.

Zaslavsky, N., Kemp, C., Tishby, N. & Regier, T. (2018). Color naming reflects both perceptual structure and communicative need. Proceedings of the 40th Annual Meeting of the Cognitive Science Society. Prize for computational modeling of language

2017

Kemp, C. & Eddy, C. (2017). A toolbox of methods for probabilistic inference. Proceedings of the 39th Annual Meeting of the Cognitive Science Society.

2015

Regier, T., Kemp C., & Kay, P. (2015). Word meanings across languages support efficient communication. In B. MacWhinney & W. O'Grady (eds.), The handbook of language emergence. Wiley.

Jern, A. & Kemp, C. (2015). A decision network account of reasoning about other people's choices. Cognition. 142, 12-38.   Video Abstract. Code and data.

Carroll, C. D. & Kemp, C. (2015). Evaluating the inverse reasoning account of object discovery. Cognition. 139, 130-153.

Xu, Y. & Kemp, C. (2015). A computational evaluation of two laws of semantic change. Proceedings of the 37th Annual Conference of the Cognitive Science Society.

2014

Lucas, C. G. & Holstein, K. and Kemp, C. (2014). Discovering hidden causes using statistical evidence. Proceedings of the 36th Annual Conference of the Cognitive Science Society.

Jern, A. & Kemp, C. (2014). Reasoning about social choices and social relationships. Proceedings of the 36th Annual Conference of the Cognitive Science Society.

2013

Carroll, C. D. & Kemp, C. (2013). Hypothesis space checking in intuitive reasoning. Proceedings of the 35th Annual Conference of the Cognitive Science Society.

2012

Lucas, C. G., Sterling, D. & Kemp, C. (2012). Superspace extrapolation reveals inductive biases in function learning. Proceedings of the 34th Annual Conference of the Cognitive Science Society.

Lucas, C. G. & Kemp, C. (2012). A unified theory of counterfactual reasoning. Proceedings of the 34th Annual Conference of the Cognitive Science Society.

Carroll, C. D. & Kemp, C. (2012). Object discovery and inverse physical reasoning. Proceedings of the 34th Annual Conference of the Cognitive Science Society.

Deverett, B. & Kemp, C. (2012). Learning deterministic causal networks from observational data. Proceedings of the 34th Annual Conference of the Cognitive Science Society.

2011

Jern, A., Lucas, C. G. & Kemp, C. (2011). Evaluating the inverse decision-making approach to preference learning. Advances in Neural Information Processing Systems 24.

Kemp, C. (2011). Inductive reasoning about chimeric creatures. Advances in Neural Information Processing Systems 24. Supporting material.   Data.

Shafto, P., Kemp, C., Mansinghka, V., & Tenenbaum, J. B. (2011). A probabilistic model of cross-categorization. Cognition. 120(1), 1-25.

Kemp, C., Han, F. & Jern, A. (2011). Concept learning and modal reasoning. Proceedings of the 33rd Annual Conference of the Cognitive Science Society.

Jern, A. & Kemp, C. (2011). Decision factors that support preference learning. Proceedings of the 33rd Annual Conference of the Cognitive Science Society.

Jern, A. & Kemp, C. (2011). Capturing mental state reasoning with influence diagrams. Proceedings of the 33rd Annual Conference of the Cognitive Science Society.

2010

Xu, Y. & Kemp, C. (2010). Inference and communication in the game of Password. Advances in Neural Information Processing Systems 23.

Kemp, C., Goodman, N. & Tenenbaum, J. (2010). Learning to learn causal models. Cognitive Science, 34(7), 1185-1243. This paper is part of a special issue on mechanisms of cognitive development.

Kemp, C., Chang, K. K. & Lombardi, L. (2010). Category and feature identification. Acta Psychologica, 133, 216-233. Data sets.

Xu, Y. & Kemp, C. (2010). Constructing spatial concepts from universal primitives. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Prize for computational modeling of language

Griffiths, T. L., Chater, N., Kemp, C., Perfors, A. & Tenenbaum, J. B. (2010). Probabilistic models of cognition: Exploring representations and inductive biases. Trends in Cognitive Sciences. 14(8), 357-364.

2009

Kemp, C. & Jern, A. (2009). Abstraction and relational learning. Advances in Neural Information Processing Systems 22.

Kemp, C. (2009). Quantification and the language of thought. Advances in Neural Information Processing Systems 22.

Jern, A., Chang, K. K. & Kemp, C. (2009). Bayesian belief polarization. Advances in Neural Information Processing Systems 22. Supporting material

Kemp, C., Jern, A. & Xu, F. (2009). Object discovery and identification. Advances in Neural Information Processing Systems 22.

Kemp, C. & Jern, A. (2009). A taxonomy of inductive problems. Proceedings of the 31st Annual Conference of the Cognitive Science Society.

Jern, A. & Kemp, C. (2009). Category generation. Proceedings of the 31st Annual Conference of the Cognitive Science Society.

Maas, A. L. & Kemp, C. (2009). One-shot learning with Bayesian networks. Proceedings of the 31st Annual Conference of the Cognitive Science Society.

Kemp, C. & Xu, F. (2009). An ideal observer model of infant object perception. Advances in Neural Information Processing Systems 21. Supporting material

2008

Kemp, C. & Tenenbaum, J. B. (2008). Structured models of semantic cognition. Behavioral and Brain Sciences. 31(6), 717-718.

Kemp, C., Goodman, N. D. & Tenenbaum, J. B. (2008). Learning and using relational theories. Advances in Neural Information Processing Systems 20. Supporting material

Griffiths, T. L., Kemp, C., & Tenenbaum, J. B. (2008). Bayesian models of cognition. In Ron Sun (ed.), The Cambridge handbook of computational cognitive modeling. Cambridge University Press.

Kemp, C., Goodman, N. D. & Tenenbaum, J. B. (2008). Theory acquisition and the language of thought. Proceedings of the 30th Annual Conference of the Cognitive Science Society.

2007

Kemp, C. (2007). The acquisition of inductive constraints. Ph.D. thesis, MIT.

Kemp, C., Goodman, N. D. & Tenenbaum, J. B. (2007). Learning causal schemata. Proceedings of the 29th Annual Conference of the Cognitive Science Society. Prize for computational modeling of high level cognition

Kemp, C., Shafto, P., Berke, A. & Tenenbaum, J. B. (2007). Combining causal and similarity-based reasoning. Advances in Neural Information Processing Systems 19. Honorable mention, Outstanding Student Paper award

Roy, D. M., Kemp, C., Mansinghka, V., & Tenenbaum, J. B. (2007). Learning annotated hierarchies from relational data. Advances in Neural Information Processing Systems 19.

2006

Kemp, C., Tenenbaum, J. B., Griffiths, T. L., Yamada, T. & Ueda, N. (2006). Learning systems of concepts with an infinite relational model. Proceedings of the 21st National Conference on Artificial Intelligence. Code and data sets.

Tenenbaum, J. B., Griffiths, T. L. & Kemp, C. (2006). Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences, 10(7), 309-318.

Kemp, C., Perfors, A. & Tenenbaum, J. B. (2006). Learning overhypotheses. Proceedings of the 28th Annual Conference of the Cognitive Science Society.

Schmidt, L. A., Kemp, C. & Tenenbaum, J. B. (2006). Nonsense and sensibility: inferring unseen possibilities. Proceedings of the 28th Annual Conference of the Cognitive Science Society.

Shafto, P., Kemp, C., Mansinghka, V., Gordon, M. & Tenenbaum, J. B. (2006). Learning cross-cutting systems of categories. Proceedings of the 28th Annual Conference of the Cognitive Science Society.

Mansinghka, V. K., Kemp, C., Tenenbaum, J. B. & Griffiths, T. L. (2006). Structured priors for structure learning. Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence.

2005

Kemp, C., Bernstein, A. & Tenenbaum, J. B. (2005). A generative theory of similarity. Proceedings of the 27th Annual Conference of the Cognitive Science Society. Stimuli and derivations.

Shafto, P., Kemp, C., Baraff, E., Coley, J. D. & Tenenbaum, J. B. (2005). Context-sensitive induction. Proceedings of the 27th Annual Conference of the Cognitive Science Society.

Kemp, C., Griffiths, T. L. & Tenenbaum, J. B. (2004). Discovering latent classes in relational data. AI Memo 2004-019

2004

Kemp, C., Perfors, A. & Tenenbaum, J. B. (2004). Learning domain structures. Proceedings of the 26th Annual Conference of the Cognitive Science Society.

Kemp, C., Griffiths, T. L., Stromsten, S., & Tenenbaum, J. B. (2004). Semi-supervised learning with trees. Advances in Neural Information Processing Systems 16. The proof of the theorem stated in the paper.

2003

Kemp, C. & Tenenbaum, J. B. (2003). Theory-based induction. Proceedings of the 25th Annual Conference of the Cognitive Science Society. Data.

2002

Kemp, C. & Ramamohanarao, K. (2002). Long term learning for web search engines. Proceedings of the 6th European Conference on Principles and Practice of Knowledge Discovery in Databases.