Research

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Publications

Portelance, E., M. Jasbi. (2023). The roles of neural networks in language acquisition. PsyArXiv:b6978.(Manuscript under review).

Portelance, E., M.C. Frank, D. Jurafsky. (2023). Learning the meanings of function words from grounded language using a Visual Question Answering model. ArXiv:2308.08628. (Manuscript under review).

Chen, X. and E. Portelance. (2023). Grammar induction pretraining for language modeling in low resource contexts. Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning(CoNLL).

Portelance, E., Y. Duan, M.C. Frank, G. Lupyan. (2023). Predicting age of acquisition for children's early vocabulary in five languages using language model surprisal. Cognitive Science.

Portelance, E.. (2022). Neural Network Approaches to the Study of Word Learning.. [Doctoral dissertation, Stanford University]. Stanford Digital Repository.

Portelance, E., M. C. Frank, D. Jurafsky, A. Sordoni, R. Laroche. (2021). The Emergence of the Shape Bias Results from Communicative Efficiency. Proceedings of the 25th Conference on Computational Natural Language Learning (CoNLL).

Potts, C., T. Icard, E. Portelance, D. Card, K. Zhou, J. Etchemendy. (2021). Philosophy of Understanding. In On the Opportunities and Risks of Foundation Models., Ed. by Center for Research on Foundation Models (CRFM) at Stanford University. arXiv:2108.07258.

Portelance, E., J. Degen, M. C. Frank. (2020). Predicting Age of Acquisition in Early Word Learning Using Recurrent Neural Networks. Proceedings of CogSci 2020.

Portelance, E. (2020). Genuine Verb stranding VP-ellipsis in Lithuanian. Proceedings of the 50th meeting of the North East Linguistic Society (NELS 50).

Portelance, E., A. Bruno, D. Harasim, L. Bergen, T. J. O'Donnell. (2019). Grammar Induction for Minimalist Grammars using Variational Bayesian Inference. arXiv:1710.11350

Harasim, D., A. Bruno, E. Portelance, M. Rohrmeier, T. J. O’Donnell. (2018). A generalised parsing framework for Abstract Grammars. arXiv:1710.11301.

Portelance, E. and A. Piper. (2016). How Cultural Capital Works: Prizewinners, Bestsellers, and the Time of Reading. Post-45.

Presentations and Posters

Portelance, E., M. C. Frank, D. Jurafsky, A. Sordoni, R. Laroche. (2021). The Emergence of the Shape Bias Results from Communicative Efficiency. Presentation at the 25th Conference on Computational Natural Language Learning (CoNLL), Punta Cana, Dominican Republic.

Portelance, E. (2021). Learning Strategies for the Emergence of Language in Iterated Learning. Presentation at the Montreal Computational & Quantitative Linguistics Lab (MCQLL), McGill University.

Portelance, E., J. Degen, M.C. Frank. (2020). Predicting Age of Acquisition in Early Word Learning Using Recurrent Neural Networks. Presentation at CogSci 2020, Virtual.

Portelance, E., J. Degen, M.C. Frank. (2020). Using neural network language models to predict age of acquisition for early vocabulary. Presentation at the International Conference for Infant Studies, Virtual.

Portelance, E., G. Kachergis, M.C. Frank. (2019). Comparing memory-based and neural network models of early syntactic development. Poster presentation at the BUCLD, Boston, MA.

Portelance, E. (2019). Verb stranding ellipsis in Lithuanian: verbal identity and head movement. Presentation at the Syntax & Semantics circle, UC Berkeley.

Portelance, E., A. Bruno, D. Harasim, L. Bergen, T. J. O’Donnell. (2018). A Framework for Lexicalized Grammar Induction Using Variational Bayesian Inference. Poster presentation at the Learning Language in Humans and Machines conference, Paris, France.

Portelance, E. (2018). On the move: Free word order in Lithuanian. Presentation at the Association for the Advancement of Baltic Studies Conference, Stanford, USA.

Portelance, E., A. Bruno, and T. J. O’Donnell. (2017). Unsupervised induction of natural language dependency structures. Poster presentation at the Montreal AI Symposium, Montreal, Canada.

Portelance, E. and A. Piper. (2017). Understanding Narrative: Computational approaches to detecting narrative frames. In proceedings of Digital Humanities Conference 2017 , Montreal, Canada.