48 citations · 130 across the 16 of their papers we have counts for
18 papers
Unsupervised Discontinuous Constituency Parsing with Mildly Context-Sensitive Grammars
Songlin Yang, Roger P. Levy, Yoon Kim
We study grammar induction with mildly context-sensitive grammars for unsupervised discontinuous parsing. Using the probabilistic linear context-free rewriting system (LCFRS) forma…
Scalable pragmatic communication via self-supervision
Jennifer Hu, Roger Levy, Noga Zaslavsky
Models of context-sensitive communication often use the Rational Speech Act framework (RSA; Frank & Goodman, 2012), which formulates listeners and speakers in a cooperative reasoni…
Linking artificial and human neural representations of language
Jon Gauthier, Roger Levy
What information from an act of sentence understanding is robustly represented in the human brain? We investigate this question by comparing sentence encoding models on a brain dec…
Representation of Constituents in Neural Language Models: Coordination Phrase as a Case Study
Aixiu An, Peng Qian, Ethan Wilcox +1
Neural language models have achieved state-of-the-art performances on many NLP tasks, and recently have been shown to learn a number of hierarchically-sensitive syntactic dependenc…
Hierarchical Representation in Neural Language Models: Suppression and Recovery of Expectations
Ethan Wilcox, Roger Levy, Richard Futrell
Deep learning sequence models have led to a marked increase in performance for a range of Natural Language Processing tasks, but it remains an open question whether they are able t…
What Syntactic Structures block Dependencies in RNN Language Models?
Ethan Wilcox, Roger Levy, Richard Futrell
Recurrent Neural Networks (RNNs) trained on a language modeling task have been shown to acquire a number of non-local grammatical dependencies with some success. Here, we provide n…