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Deep autoregressive sequence-to-sequence models have demonstrated impressive performance across a wide variety of tasks in recent years.
Distilling the knowledge in a neural network
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Deep learning face attributes in the wild
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A neural attention model for abstractive sentence summarization
Alexander M Rush, Sumit Chopra, and Jason Weston · 2015
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Sequence-level knowledge distillation
Yoon Kim and Alexander M Rush · 2016
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Aäron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alexander Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu · 2016
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Efficient neural audio synthesis
Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aaron van den Oord, Sander Dieleman, and Koray Kavukcuoglu · 2018
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Deterministic non-autoregressive neural sequence modeling by iterative refinement
Jason Lee, Elman Mansimov, and Kyunghyun Cho · 2018
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Ashish Vaswani, Samy Bengio, Eugene Brevdo, Francois Chollet, Aidan N. Gomez, Stephan Gouws, Llion Jones, Łukasz Kaiser, Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, and Jakob Uszkoreit · 2018
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