3 papers
cs.CL2020
Probabilistic Predictions of People Perusing: Evaluating Metrics of Language Model Performance for Psycholinguistic Modeling
Yiding Hao, Simon Mendelsohn, Rachel Sterneck +2
By positing a relationship between naturalistic reading times and information-theoretic surprisal, surprisal theory (Hale, 2001; Levy, 2008) provides a natural interface between la…
cs.CL2019
Finding Syntactic Representations in Neural Stacks
William Merrill, Lenny Khazan, Noah Amsel +3
Neural network architectures have been augmented with differentiable stacks in order to introduce a bias toward learning hierarchy-sensitive regularities. It has, however, proven d…
cs.NE2018
Context-Free Transductions with Neural Stacks
Yiding Hao, William Merrill, Dana Angluin +4
This paper analyzes the behavior of stack-augmented recurrent neural network (RNN) models. Due to the architectural similarity between stack RNNs and pushdown transducers, we train…