Publications

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F Foundations
P Perception
E Education
CI Causal Induction
CD Cognitive Development
PR Probabilistic Reasoning
RPM Rational Process Models
S&C Similarity and Categorization
SML Statistical Models of Language
NBM Nonparametric Bayesian Models
CEIL Cultural Evolution and Iterated Learning
DRLM Decision Making and Reinforcement Learning

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Statistical Models of Language
SML
Hawkins, R. D., Franke, M., Frank, M. C., Smith, K., Griffiths, T. L., & Goodman, N. D. (preprint). From partners to populations: A hierarchical Bayesian account of coordination and convention. (link)
SML
Nematzadeh, A., Shekarchi, Z., Griffiths, T. L., & Stevenson, S. (preprint). Competition in Cross-situational Word Learning: A Computational Study. (link)
SML
Meylan, S., & Griffiths, T. (preprint). The challenges of large-scale, web-based language datasets: Word length and predictability revisited. (link)
SML
Meylan, S. C., & Griffiths, T. L. (preprint). Word forms - not just their lengths - are optimized for efficient communication. (link)
SML
Meylan, S. C., Nair, S., & Griffiths, T. L. (in press). Evaluating models of robust word recognition with serial reproduction. Cognition, 210, 104553.(pdf)
SML
DRLM
Sumers, T. R., Ho, M. K., Hawkins, R.D., Narasimhan, K., & Griffiths, T. L. (2021). Learning rewards from linguistic feedback. Proceedings of the 35th AAAI Conference on Artificial Intelligence. (pdf)
S&C
SML
Peterson, J. C., Chen, D., & Griffiths, T. L. (2020). Parallelograms revisited: Exploring the limitations of vector space models for simple analogies. Cognition, 205, 104440. (pdf)
SML
McCoy, R. T., Grant, E., Smolensky, P., Griffiths, T. L., & Linzen, T. (2020). Universal linguistic inductive biases via meta-learning. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
SML
CEIL
Hawkins, R. D., Goodman, N. D., Goldberg, A. E., & Griffiths, T. L. (2020). Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks. Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pdf)
SML
Hawkins, R. D.*, Yamakoshi, T.*, Griffiths, T. L., & Goldberg, A. E. (2020). Investigating representations of verb bias in neural language models. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). (pdf)
SML
Nematzadeh, A., Burns, K., Grant, E., Gopnik, A., & Griffiths, T. L. (2018). Evaluating theory of mind in question answering. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. (pdf)
S&C
SML
Peterson, J. C., Soulos, P., Nematzadeh, A., & Griffiths, T. L. (2018). Learning hierarchical visual representations in deep neural networks using hierarchical linguistic labels. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
PR
SML
Gates, M. A., Veuthey, T. L., Tessler, M. H., Smith, K. A., Gerstenberg, T., Bayet, L., & Tenenbaum, J. B. (2018). Tiptoeing around it: Inference from absence in potentially offensive speech. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf)
SML
de Heer, W. A., Huth, A. G., Griffiths, T. L., Gallant, J. L., & Theunissen, F. E. (2017). The hierarchical cortical organization of human speech processing. Journal of Neuroscience, 37(27), 6539-6557. (pdf)
SML
CEIL
Whalen, A., & Griffiths, T. L. (2017). Adding population structure to models of language evolution by iterated learning. Journal of Mathematical Psychology, 76, 1-6. (pdf)
CD
SML
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)
SML
Nematzadeh, A., Meylan, S. C., & Griffiths, T. L. (2017). Evaluating vector-space models of word representation, or the unreasonable effectiveness of counting words near other words. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
S&C
SML
Chen, D., Peterson, J. C., & Griffiths, T. L. (2017). Evaluating vector-space models of analogy. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf)
SML
Huth, A. G., de Heer, W. A., Griffiths, T. L., Theunissen, F. E., & Gallant, J. L. (2016). Natural speech reveals the semantic maps that tile the human cerebral cortex. Nature, 532 453-458. (pdf)
PR
SML
Hsu, A., & Griffiths, T. L. (2016). Sampling assumptions affect use of indirect negative evidence in language learning PLOS One, 11(6). (pdf)
SML
Cibelli, E., Xu, Y., Austerweil, J. L., Griffiths, T. L., & Regier, T. (2016). The Sapir-Whorf Hypothesis and probabilistic inference: Evidence from the domain of color. PLOS One, 11(7). (pdf)
RPM
SML
Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2015). Random walks on semantic networks can resemble optimal foraging. Psychological Review, 122, 558-569. (pdf)
CI
SML
NBM
Buchsbaum, D., Griffiths, T. L., Plunkett, D., Gopnik, A., & Baldwin, D. (2015). Inferring action structure and causal relationships in continuous sequences of human action. Cognitive Psychology, 76, 30-77. (pdf)
CD
SML
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)
SML
CEIL
Rafferty, A. N., Griffiths, T. L., & Klein, D. (2014). Analyzing the rate at which languages lose the influence of a common ancestor. Cognitive Science, 38, 1406-1431. (pdf)
SML
CEIL
Maurits, L., & Griffiths, T. L. (2014). Tracing the roots of syntax with Bayesian phylogenetics. Proceedings of the National Academy of Sciences, 111, 13576-13581. (pdf)
RPM
SML
Bourgin, D. D., Abbott, J. T., Griffiths, T. L., Smith, K. A., & Vul, E. (2014). Empirical evidence for Markov chain Monte Carlo in memory search. Proceedings of the 36th Annual Conference of the Cognitive Science Society. (pdf)
SML
NBM
Feldman, N. H., Griffiths, T. L., Goldwater, S., & Morgan, J. (2013). A role for the developing lexicon in phonetic category acquisition. Psychological Review, 120, 751-778. (pdf)
SML
CEIL
Rafferty, A. N., Griffiths, T. L., & Ettlinger, M. (2013). Greater learnability is not sufficient to produce cultural universals. Cognition, 129, 70-87. (pdf)
S&C
SML
Feldman, N. H., Myers, E. B., White, K. S., Griffiths, T. L., & Morgan, J. L. (2013). Word-level information influences phonetic learning in adults and infants. Cognition, 127, 427-438. (pdf)
SML
CEIL
Bouchard-Cote, A., Hall, D., Griffiths, T. L., & Klein, D. (2013) Automated reconstruction of ancient languages using probabilistic models of sound change. Proceedings of the National Academy of Sciences. (pdf)
RPM
SML
Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2012). Human memory search as a random walk in a semantic network. Advances in Neural Information Processing Systems, 25. (pdf)
SML
NBM
Goldwater, S., Griffiths, T. L., Johnson, M. (2011). Producing power-law distributions and damping word frequencies with two-stage language models. Journal of Machine Learning Research, 12, 2335-2382. (pdf)
SML
Feldman, N. H., Myers, E., White, K., Griffiths, T. L., & Morgan, J. L. (2011). Learners use word-level statistics in phonetic category acquisition. Proceedings of the 35th Boston University Conference on Language Development. (pdf)
SML
Griffiths, T. L. (2011). Rethinking language: How probabilities shape the words we use. Proceedings of the National Academy of Sciences, 108, 3825-3826. (pdf)
SML
CEIL
Griffiths, T. L., & Reali, F. (2011). Modelling minds as well as populations. Proceedings of the Royal Society, Series B. (pdf)
P
SML
Buchsbaum, D., Canini, K. R., & Griffiths, T. L. (2011). Segmenting and recognizing human action using low-level video features. Proceedings of the 33rd Annual Conference of the Cognitive Science Society.(pdf)
SML
CEIL
Rafferty, A. N., Griffiths, T. L., & Ettlinger, M. (2011) Exploring the relationship between learnability and linguistic universals. Proceedings of the 2nd Workshop on Cognitive Modeling and Computational Linguistics at ACL 2011. (pdf)
SML
NBM
Frank, M., Goldwater, S., Griffiths, T. L., & Tenenbaum, J. B. (2010). Modeling human performance in statistical word segmentation. Cognition, 117, 107-125.(pdf)
SML
Rosen-Zvi, M., Chemudugunta, C., Griffiths, T. L., Smyth, P., & Steyvers, M. (2010). Learning author-topic models from text corpora. ACM Transactions on Information Systems, 28(1), Article 4. (pdf)
SML
CEIL
Burkett, D., & Griffiths, T. L. (2010). Iterated learning of multiple languages from multiple teachers. Evolang 8. (pdf)
SML
NBM
Blei, D. M., Griffiths, T. L., & Jordan, M. I. (2010). The nested Chinese restaurant process and Bayesian nonparametric inference of topic hierarchies. Journal of the ACM, 57, 1-30.(pdf)
SML
CEIL
Reali, F., & Griffiths, T. L. (2010). Words as alleles: Connecting language evolution with Bayesian learners to models of genetic drift. Proceedings of the Royal Society, Series B, 277, 429-436. (pdf)
CD
SML
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)
SML
Hsu, A., & Griffiths, T. L. (2009). Differential use of implicit negative evidence in generative and discriminative language learning. Advances in Neural Information Processing Systems 22. (pdf)
P
S&C
SML
Feldman, N. H., Griffiths, T. L., & Morgan, J. L. (2009). The influence of categories on perception: Explaining the perceptual magnet effect as optimal statistical inference. Psychological Review, 116, 752-782. (pdf)
CD
SML
Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian framework for word segmentation: Exploring the effects of context. Cognition, 112, 21-54. (pdf)
SML
CEIL
Reali, F., & Griffiths, T. L. (2009). The evolution of linguistic frequency distributions: Relating regularization to inductive biases through iterated learning. Cognition, 111, 317-328. (pdf)
SML
Canini, K. R., Shi, L., & Griffiths, T. L. (2009). Online inference of topics with Latent Dirichlet Allocation. AISTATS. (pdf)
RPM
SML
Levy, R., Reali, F., & Griffiths, T. L. (2009). Modeling the effects of memory on human online sentence processing with particle filters. Advances in Neural Information Processing Systems 21. (pdf)
CI
SML
NBM
Buchsbaum, D., Griffiths, T. L., Gopnik, A., & Baldwin, D. (2009). Learning from actions and their consequences: Inferring causal variables from continuous sequences of human action. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf)
SML
NBM
Feldman, N. H., Griffiths, T. L., & Morgan, J. L. (2009). Learning phonetic categories by learning a lexicon. Proceedings of the 31st Annual Conference of the Cognitive Science Society. (pdf)
SML
CEIL
Bouchard-Cote, A., Griffiths, T. L., & Klein, D. (2009). Improved reconstruction of protolanguage word forms. Proceedings of the North American Conference on Computational Linguistics (NAACL'09). (pdf)
SML
Dowman, M., Savova, V., Griffiths, T. L., Kording, K. P., Tenenbaum, J. B., & Purver, M. (2008). A probabilistic model of meetings that combines words and discourse features. IEEE Transactions on Audio, Speech, and Language Processing, 16, 1238-1248. (pdf)
SML
CEIL
Bouchard-Cote, A., Liang, P., Griffiths, T. L., & Klein, D. (2008). A probabilistic approach to language change. Advances in Neural Information Processing Systems 20. (pdf)
SML
Steyvers, M., & Griffiths, T. L. (2008). Rational analysis as a link between human memory and information retrieval. In M. Oaksford and N. Chater (Eds.). The probabilistic mind: Prospects for rational models of cognition. Oxford: Oxford University Press. (pdf)
SML
CEIL
Reali, F., & Griffiths, T. L. (2008). The evolution of frequency distributions: Relating regularization to inductive biases through iterated learning. Proceedings of the 30th Annual Conference of the Cognitive Science Society. (pdf)
SML
Griffiths, T. L., Steyvers, M., & Firl, A. (2007). Google and the mind: Predicting fluency with PageRank. Psychological Science, 18, 1069-1076. (pdf)
S&C
SML
Iwata, T., Saito, K., Ueda, N., Stromsten, S., Griffiths, T. L., & Tenenbaum, J. B. (2007). Parametric embedding for class visualization. Neural Computation, 19, 2536-2556. (pdf)
SML
NBM
Johnson, M., Griffiths, T. L., & Goldwater, S (2007). Adaptor grammars: A framework for specifying compositional nonparametric Bayesian models. Advances in Neural Information Processing Systems 19. (pdf)
SML
Griffiths, T. L., Steyvers, M., & Tenenbaum, J. B. (2007). Topics in semantic representation. Psychological Review, 114,211-244. (pdf) (topic modeling toolbox)
SML
Steyvers, M., & Griffiths, T. L. (2007). Probabilistic topic models. In T. L.andauer, D. S. McNamara, S. Dennis, & W. Kintsch (Eds.), Handbook of Latent Semantic Analysis. Hillsdale, NJ: Erlbaum. (pdf) (topic modeling toolbox)
SML
Goldwater, S., Griffiths, T. L., & Johnson, M. (2007). Distributional cues to word segmentation: Context is important. Proceedings of the 31st Boston University Conference on Language Development. (pdf)
SML
CEIL
Bouchard, A., Liang, P., Griffiths, T., & Klein, D. (2007). A probabilistic approach to diachronic phonology. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). (pdf)
SML
Frank, M. C., Goldwater, S., Mansinghka, V., Griffiths, T., & Tenenbaum, J. B. (2007). Modeling human performance in statistical word segmentation. Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. (pdf)
S&C
SML
Feldman, N. H., & Griffiths, T. L. (2007). A rational account of the perceptual magnet effect. Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. (pdf)
CD
SML
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)
SML
Johnson, M., Griffiths, T. L., & Goldwater, S. (2007). Bayesian inference for PCFGs via Markov chain Monte Carlo. Proceedings of the North American Conference on Computational Linguistics (NAACL'07). (pdf)
SML
Steyvers, M., Griffiths, T. L., & Dennis, S. (2006). Probabilistic inference in human semantic memory. Trends in Cognitive Science, 10, 327-334. (pdf) (topic modeling toolbox)
CD
SML
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)
SML
Purver, M., Kording, K. P., Griffiths, T. L., & Tenenbaum, J. B. (2006). Unsupervised topic modelling for multi-party spoken discourse. Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. (pdf)
SML
NBM
Goldwater, S., Griffiths, T. L., & Johnson, M. (2006). Contextual dependencies in unsupervised word segmentation. Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics.(pdf)
SML
Iwata, T., Saito, K., Ueda, N., Stromsten, S., Griffiths, T. L., & Tenenbaum, J. B. (2005). Parametric embedding for class visualization. Advances in Neural Information Processing Systems 17. (pdf)
SML
Griffiths, T. L., Steyvers, M., Blei, D. M., & Tenenbaum, J. B. (2005). Integrating topics and syntax. Advances in Neural Information Processing Systems 17. (pdf) (topic modeling toolbox)
SML
NBM
Blei, D. M., Griffiths, T. L., Jordan, M. I., & Tenenbaum, J. B. (2004). Hierarchical topic models and the nested Chinese restaurant process. Advances in Neural Information Processing Systems 16. (pdf) (winner of the Best Student Paper prize)
SML
Steyvers, M., Smyth, P., Rosen-Zvi, M., & Griffiths, T. L. (2004). Probabilistic Author-Topic models for information discovery. The Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (pdf) (demo) (topic modeling toolbox)
SML
Rosen-Zvi, M., Griffiths, T. L., Steyvers, M., & Smyth, P. (2004). The Author-Topic Model for authors and documents. 20th Conference on Uncertainty in Artificial Intelligence. (pdf) (demo) (topic modeling toolbox)
SML
Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101, 5228-5235. (pdf) (topic modeling toolbox)
SML
Griffiths, T. L., & Steyvers, M. (2003). Prediction and semantic association. Advances in Neural Information Processing Systems 15. (pdf) (topic modeling toolbox)
SML
Griffiths, T. L., & Tenenbaum, J. B. (2002). Using vocabulary knowledge in Bayesian multinomial estimation. Advances in Neural Information Processing Systems, 14. (pdf)
SML
Griffiths, T. L., & Steyvers, M. (2002). A probabilistic approach to semantic representation. Proceedings of the 24th Annual Conference of the Cognitive Science Society. (pdf) (topic modeling toolbox)

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