40 citations · 100 across the 20 of their papers we have counts for
4 papers · 1 filter
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…
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
Ethan Wilcox, Peng Qian, Richard Futrell +2
State-of-the-art LSTM language models trained on large corpora learn sequential contingencies in impressive detail and have been shown to acquire a number of non-local grammatical…
Neural Language Models as Psycholinguistic Subjects: Representations of Syntactic State
Richard Futrell, Ethan Wilcox, Takashi Morita +3
We deploy the methods of controlled psycholinguistic experimentation to shed light on the extent to which the behavior of neural network language models reflects incremental repres…