Fetching the paper…
Reading the bibliography…
In this work, we examine methods for data augmentation for text-based tasks such as neural machine translation (NMT).
A maximum entropy approach to natural language processing
Adam L Berger, Vincent J Della Pietra, and Stephen A Della Pietra. 1996 · 1996
Earlier work this paper cites.
Semi-supervised learning (chapelle, o. et al., eds.; 2006)[book reviews]
Olivier Chapelle, Bernhard Scholkopf, and Alexander Zien. 2009 · 2006
Earlier work this paper cites.
Better hypothesis testing for statistical machine translation: Controlling for optimizer instability
Jonathan Clark, Chris Dyer, Alon Lavie, and Noah Smith. 2011 · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2012 · 2012
Earlier work this paper cites.
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. 2014 · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Lei Ba. 2015 · 2015
Earlier work this paper cites.
Stanford neural machine translation systems for spoken language domain
Minh-Thang Luong and Christopher D. Manning. 2015 · 2015
Earlier work this paper cites.
Effective approaches to attention-based neural machine translation
Minh-Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Deep speech 2: End-to-end speech recognition in english and mandarin
Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, and more authors. 2016 · 2016
Cited alongside, same era.
A theoretically grounded application of dropout in recurrent neural networks
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
Cited alongside, same era.
Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens van der Maaten, and Kilian Q. Weinberger. 2016 · 2016
Cited alongside, same era.
Reward augmented maximum likelihood for neural structured prediction
Mohammad Norouzi, Samy Bengio, Zhifeng Chen, Navdeep Jaitly, Mike Schuster, Yonghui Wu, and Dale Schuurmans. 2016 · 2016
Cited alongside, same era.
Sequence level training with recurrent neural networks
Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W. Taylor. 2017 · 2017
Later among the works it cites.
Data augmentation for low-resource neural machine translation
Marzieh Fadaee, Arianna Bisazza, and Christof Monz. 2017 · 2017
Later among the works it cites.
Softmax q-distribution estimation for structured prediction: A theoretical interpretation for raml
Xuezhe Ma, Pengcheng Yin, Jingzhou Liu, Graham Neubig, and Eduard Hovy. 2017 · 2017
Later among the works it cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Later among the works it cites.
Synthetic and natural noise both break neural machine translation
Yonatan Belinkov and Yonatan Bisk. 2018 · 2018
Closest in time.
Non-autoregressive neural machine translation
Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K. Li, and Richard Socher. 2018 · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2016 · 2016
Cited alongside, same era.
Wide residual networks
Sergey Zagoruyko and Nikos Komodakis. 2016 · 2016
Cited alongside, same era.
Edinburgh neural machine translation systems for wmt 16
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016a
Cited in the paper.
Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016b
Cited in the paper.
Closest in time.
Investigating backtranslation in neural machine translation
Alberto Poncelas, Dimitar Shterionov, Andy Way, Gideon Maillette de Buy Wenniger, and Peyman Passban. 2018 · 2018
Closest in time.