Harootonian, S. K., Niv, Y., Griffiths, T., & Ho, M. K. (2024). Modeling Cognitive Strategies in Teaching: Integrating Theory of Mind and Heuristics. 46th Annual Meeting of the Cognitive Science Society. (pdf)
Zhao, B., Vélez, N., & Griffiths, T. L. (2024). Comparing Human Behavior to an Optimal Policy for Innovation. Proceedings of the AAAI Symposium Series, 3(1), 598-599. (pdf)
Grant, E., Nematzadeh, A., & Griffiths, T. L. (2017). How can memory-augmented neural networks pass a false-belief task? Proceedings of the 39th Annual Conference of the Cognitive Science Society.(pdf)
Foushee, R., Griffiths, T. L., & Srinivasan, M. (2016). Lexical complexity of child-directed and overheard speech: Implications for learning. Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf)
Gopnik, A., Griffiths, T. L., & Lucas, C. G. (2015). When younger learners can be better (or at least more open-minded) than older ones. Current Directions in Psychological Science, 24, 87-92. (pdf)
Hu, J., Whalen, A., Buchsbaum, D., Griffiths, T. L., & Xu, F. (2015). Can children balance the size of a majority with the quality of their information? Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
Lieder, F., Sim, Z., Hu, J. C., & Griffiths, T. L. (2015). Children and adults differ in their strategies for social learning. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
Meylan, S. C., & Griffiths, T. L. (2015). A Bayesian framework for learning words from multiword utterances. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
Ruggeri, A., Lombrozo, T., Griffiths, T. L., & Xu, F. (2015). Children search for information as efficiently as adults, but seek additional confirmatory evidence. Proceedings of the 37th Annual Conference of the Cognitive Science Society. (pdf)
Bonawitz, E., Denison, S., Griffiths, T. L., & Gopnik, A. (2014). Probabilistic models, learning algorithms, and response variability: Sampling in cognitive development. Trends in Cognitive Sciences, 18, 497-500. (pdf)
Lucas, C. G., Bridgers, S., Griffiths, T. L., & Gopnik, A. (2014). When children are better (or at least more open-minded) learners than adults: Developmental differences in learning the forms of causal relationships. Cognition, 131, 284-299. (pdf)
Bonawitz, E., Gopnik, A., Denison, S., & Griffiths, T. L. (2012). Rational randomness: The role of sampling in an algorithmic account of preschoolers' causal learning. In F. Xu (Ed.) Rational constructivism in cognitive development. Waltham, MA: Academic Press. (book)
Rafferty, A. N., & Griffiths, T. L. (2010). Optimal language learning: The importance of starting representative. Proceedings of the 32nd Annual Conference of the Cognitive Science Society.(pdf)
Buchsbaum, D., Gopnik, A., & Griffiths, T. L. (2010). Children's imitation of action sequences is influenced by statistical evidence and inferred causal structure. Proceedings of the 32nd Annual Conference of the Cognitive Science Society.(pdf)
Lucas, C. G., Gopnik, A., & Griffiths, T. L. (2010). Developmental differences in learning the forms of causal relationships. Proceedings of the 32nd Annual Conference of the Cognitive Science Society.(pdf)
Lucas, C., Griffiths, T. L., Xu, F., & Fawcett, C. (2009). A rational model of preference learning and choice prediction by children. Advances in Neural Information Processing Systems 21.(pdf)
Schulz, L. E., Bonawitz, E. B., & Griffiths, T. L. (2007). Can being scared make your tummy ache? Naive theories, ambiguous evidence and preschoolers' causal inferences. Developmental Psychology, 43, 1124-1139. (pdf)
Goldwater, S., & Griffiths, T. L. (2007). A fully Bayesian approach to unsupervised part-of-speech tagging. Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL'07).(pdf)
Goldwater, S., Griffiths, T. L., & Johnson, M. (2006). Interpolating between types and tokens by estimating power law generators. Advances in Neural Information Processing Systems 18. (pdf) (note: this version of the paper is slightly modified from the hardcopy proceedings)
Bonawitz, E. B., Griffiths, T. L., & Schulz, L. (2006). Modeling cross-domain causal learning in preschoolers as Bayesian inference. Proceedings of the 28th Annual Conference of the Cognitive Science Society.(pdf) (winner of the Marr Prize for best student paper)