Fetching the paper…
Reading the bibliography…
Recurrent neural networks have been very successful at predicting sequences of words in tasks such as language modeling.
Numerical methods for computing angles between linear subspaces
A ∘ \accentset{\circ}{\text{A}} ke Björck and Gene H Golub · 1973
Earlier work this paper cites.
Building a large annotated corpus of english: The penn treebank
Mitchell P Marcus, Mary Ann Marcinkiewicz, and Beatrice Santorini · 1993
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, and Pascal Vincent · 2001
Earlier work this paper cites.
Three new graphical models for statistical language modelling
Andriy Mnih and Geoffrey Hinton · 2007
Earlier work this paper cites.
Recurrent neural network based language model
Tomas Mikolov, Martin Karafiát, Lukas Burget, Jan Cernockỳ, and Sanjeev Khudanpur · 2010
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Earlier work this paper cites.
Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Y Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts · 2013
Earlier work this paper cites.
Language modeling with sum-product networks
Wei-Chen Cheng, Stanley Kok, Hoai Vu Pham, Hai Leong Chieu, and Kian Ming Adam Chai · 2014
Cited alongside, same era.
On the properties of neural machine translation: Encoder-decoder approaches
Kyunghyun Cho, Bart Van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio · 2014
Cited alongside, same era.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
Cited alongside, same era.
Recurrent neural network regularization
Wojciech Zaremba, Ilya Sutskever, and Oriol Vinyals · 2014
Cited alongside, same era.
Learning with a wasserstein loss
Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya, and Tomaso A Poggio · 2015
Cited alongside, same era.
A neural attention model for abstractive sentence summarization
Alexander M Rush, Sumit Chopra, and Jason Weston · 2015
Later among the works it cites.
Multi-way, multilingual neural machine translation with a shared attention mechanism
Orhan Firat, Kyunghyun Cho, and Yoshua Bengio · 2016
Closest in time.
Improved learning through augmenting the loss
Hakan Inan and Khashayar Khosravi · 2016
Closest in time.
Lstm, gru, highway and a bit of attention: an empirical overview for language modeling in speech recognition
Kazuki Irie, Zoltán Tüske, Tamer Alkhouli, Ralf Schlüter, and Hermann Ney · 2016
Closest in time.
Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher · 2016
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yarin Gal · 2015
Cited alongside, same era.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
Cited alongside, same era.
Character-aware neural language models
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M Rush · 2015
Cited alongside, same era.
Essai sur la géométrie à n n dimensions
Camille Jordan
Cited in the paper.
Context dependent recurrent neural network language model
Tomas Mikolov and Geoffrey Zweig
Cited in the paper.
How to construct deep recurrent neural networks
Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, and Yoshua Bengio
Cited in the paper.
On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio
Cited in the paper.
Abstractive text summarization using sequence-to-sequence rnns and beyond
Ramesh Nallapati, Bowen Zhou, Çaglar Gulçehre, and Bing Xiang · 2016
Closest in time.
Using the output embedding to improve language models
Ofir Press and Lior Wolf · 2016
Closest in time.
Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutník, and Jürgen Schmidhuber · 2016
Closest in time.