479 citations · 993 across the 4 of their papers we have counts for
4 papers
A Way out of the Odyssey: Analyzing and Combining Recent Insights for LSTMs
Shayne Longpre, Sabeek Pradhan, Caiming Xiong +1
LSTMs have become a basic building block for many deep NLP models. In recent years, many improvements and variations have been proposed for deep sequence models in general, and LST…
Quasi-Recurrent Neural Networks
James Bradbury, Stephen Merity, Caiming Xiong +1
Recurrent neural networks are a powerful tool for modeling sequential data, but the dependence of each timestep's computation on the previous timestep's output limits parallelism a…
Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling
Hakan Inan, Khashayar Khosravi, Richard Socher
Recurrent neural networks have been very successful at predicting sequences of words in tasks such as language modeling. However, all such models are based on the conventional clas…
Pointer Sentinel Mixture Models
Stephen Merity, Caiming Xiong, James Bradbury +1
Recent neural network sequence models with softmax classifiers have achieved their best language modeling performance only with very large hidden states and large vocabularies. Eve…