selected publications

2022
  1. Synthesizing theories of human language with Bayesian program induction Kevin Ellis, Adam Albright, Armando Solar-Lezama, Joshua B. Tenenbaum, and Timothy J. O’Donnell Nature Communications. 1–13. 2022. [link]
  2. Compositional generalization in dependency parsing Emily Goodwin, Timothy J. O’Donnell, Siva Reddy, and Dzmitry Bahdanau In Proceedings of the 60th annual Meeting of the Association for Computational Linguistics (ACL 2022). Dublin, Ireland. 2022. [link]
  3. Evaluating distributional distortion in neural language modeling Benjamin Lebrun, Alessandro Sordoni, and Timothy J. O’Donnell In Proceedings of 10th International Conference on Learning Representations (ICLR 2022). 2022. [link]
  4. Characterizing idioms: Conventionality and contingency Michaela Socolof, Jackie Chi Kit Cheung, Michael Wagner, and Timothy J. O’Donnell In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022). Dublin, Ireland. 2022. [link]
  5. Measuring morphological fusion using partial information decomposition Michaela Socolof, Jacob L. Hoover, Alessandro Sordoni, Richard Futrell, and Timothy J. O’Donnell In Proceedings of the 29th International Conference on Computational Linguistics (COLING 2022). 2022.
2021
  1. Jointly learning truth-conditional denotations and groundings using parallel attention Leon Bergen, Dzmitry Bahdanau, and Timothy J. O’Donnell arXiv. 2021. [link]
  2. Systematic generalization with Edge Transformers Leon Bergen, Timothy J. O’Donnell, and Dzmitry Bahdanau In Advances in Neural Information Processing Systems (NeurIPS 2021). 2021. [link]
  3. Linguistic dependencies and statistical dependence Jacob L. Hoover, Wenyu Du, Alessandro Sordoni, and Timothy J. O’Donnell In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021). Online and Punta Cana, Dominican Republic. Nov, 2021. [link]
2020
  1. CLOSURE: Assessing systematic generalization of CLEVR models Dzmitry Bahdanau, Harm Vries, Timothy J. O’Donnell, Shikhar Murty, Philippe Beaudoin, Yoshua Bengio, and Aaron Courville arXiv. 2020. [link]
  2. Exploiting syntactic structure for better language modeling: A syntactic distance approach Wenyu Du, Zhouhan Lin, Yikang Shen, Timothy J. O’Donnell, Yoshua Bengio, and Yue Zhang In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020). Online. 2020. [link]
  3. Probing linguistic systematicity Emily Goodwin, Koustuv Sinha, and Timothy J. O’Donnell In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Online. 2020. [link]
  4. The Jazz Harmony Treebank Daniel Harasim, C. Finkensiep, P. Ericson, Timothy J. O’Donnell, and Martin Rohrmeier In Proceedings of the 21st Annual Conference of the International Society for Music Information Retrieval (ISMIR 2020). Montreal, Canada. 2020. [link]
  5. Statistical evidence for learnable lexical subclasses in Japanese Takashi Morita, and Timothy J. O’Donnell Linguistic Inquiry. 87–120. 2020. [link]
  6. Recursive top-down production for sentence generation with latent trees Shawn Tan, Timothy J. O’Donnell, Alessandro Sordoni, and Aaron Courville In Findings of the Association for Computational Linguistics: EMNLP 2020. 2020. [link]
2019
  1. Harmonic syntax in time: Rhythm improves grammatical models of harmony Daniel Harasim, Timothy J. O’Donnell, and Martin Rohrmeier 2019. [link]
  2. A thousand studies for the price of one: Accelerating psychological science with Pushkin. Joshua K. Hartshorne, Josh Leeuw, Mariela Jennings, Noah D. Goodman, and Timothy J. O’Donnell Behavioral Research Methods. 2019. [link]
  3. Universality and diversity in human song Samuel A. Mehr, Manvir Singh, Dean Knox, Daniel M. Ketter, Daniel Pickens-Jones, Stephanie Atwood, Christopher Lucas, Nori Jacoby, Alena A. Egner, Erin J. Hopkins, Rhea M. Howard, Timothy J. O’Donnell, Steven Pinker, Max M. Krasnow, and Luke Glowacki Science. 1–17. 2019. [link]
  4. Morphological irregularity correlates with frequency Shijie Wu, Ryan Cotterell, and Timothy J. O’Donnell In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019). 2019. [link]
  5. Five ways in which computational models can help advancing Artificial Grammar Learning research Willem H. Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Timothy J. O’Donnell, Tim Sainburg, and Timothy Q. Gentner Topics in Cognitive Science. 1–17. 2019. [link]
2018
  1. A maximum likelihood model for the harmonic analysis of symbolic music Colin C. Aitken, Timothy J. O’Donnell, and Martin Rohrmeier In Proceedings of the 15th Sound and Music Computing Conference (SMC 2018). Limassol, Cyprus. 2018.
  2. A generalized parsing framework for generative models of harmonic syntax Daniel Harasim, Martin Rohrmeier, and Timothy J. O’Donnell In Proceedings of the 19th Annual Conference of the International Society for Music Information Retrieval (ISMIR 2018). Paris, France. 2018. [link]
2017
  1. A generative model of phonotactics Richard Futrell, Adam Albright, Peter Graff, and Timothy J. O’Donnell Transaction of the Association for Computational Linguistics. 73–86. 2017. [link]
  2. Evaluating hierarchies of verb argument structure with hierarchical clustering Jesse Mu, Joshua K. Hartshorne, and Timothy J. O’Donnell In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP 2017). Copenhagen, Denmark. 2017. [link]
2016
  1. Psych verbs, the linking problem, and the acquisition of language Joshua K. Hartshorne, Timothy J. O’Donnell, Yasutada Sudo, Miki Uruwashi, Miseon Lee, and Jesse Snedeker Cognition. 268–2888. 2016.
2015
  1. Unsupervised Lexicon Discovery from Acoustic Input Chia-Ying Lee, Timothy J. O’Donnell, and James R. Glass Transaction of the Association for Computational Linguistics. 389–403. 2015.
  2. A model of rapid phonotactic generalization. Tal Linzen, and Timothy J. O’Donnell In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2015). 2015.
  3. Evaluating models of computation and storage in human sentence processing Luong Min-Thang, Timothy J. O’Donnell, and Noah D. Goodman In Proceedings of the Workshop on Cognitive Aspects of Computational Language Learning. 2015. [link]
  4. Productivity and Reuse in Language: A Theory of Linguistic Computation and Storage Timothy J. O’Donnell The MIT Press. Cambridge, Massachusetts. 2015.
2013
  1. Arguments and Modifiers from the Learner’s Perspective Leon Bergen, Edward Gibson, and Timothy J. O’Donnell In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics. 115-119. Sofia, Bulgaria. 2013.
  2. Learning Non-concatenative morphology Michelle Fullwood, and Timothy J. O’Donnell Sofia, Bulgaria. 2013.
2011
  1. Productivity and Reuse in Language Timothy J. O’Donnell, Jesse Snedeker, Joshua B. Tenenbaum, and Noah D. Goodman In Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Boston, MA. 2011.
  2. Storage and computation in syntax: Evidence from relative clause priming. Melissa Troyer, Timothy J. O’Donnell, Evelina Fedorinko, and Edward Gibson In roceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. 336–341. Boston, Massachusetts. 2011.
2009
  1. Fragment Grammars: Exploring Computation and Reuse in Language Timothy J. O’Donnell, Noah D. Goodman, and Joshua B. Tenenbaum Cambridge, MA. 2009.
2007
  1. Evolutionary Linguistics: a new look at an old landscape Marc D. Hauser, David Barner, and Timothy J. O’Donnell Language Learning and Development. 2007.
2005
  1. Using Mathematical Models of Language Experimentally Timothy J. O’Donnell, Marc D. Hauser, and W. Tecumseh Fitch Trends in Cognitive Sciences. 284-289. Jun, 2005.