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Supervised training of abstractive language generation models results in learning conditional probabilities over language sequences based on the supervised training signal.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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English gigaword corpus
David Graff and C Cieri. 2003 · 2003
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Frustratingly easy domain adaptation
Hal Daumé III. 2009 · 2009
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Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer. 2011 · 2011
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Domain adaptation for large-scale sentiment classification: A deep learning approach
Xavier Glorot, Antoine Bordes, and Yoshua Bengio. 2011 · 2011
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Annotated gigaword
Courtney Napoles, Matthew Gormley, and Benjamin Van Durme. 2012 · 2012
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Dlid: Deep learning for domain adaptation by interpolating between domains
Sumit Chopra, Suhrid Balakrishnan, and Raghuraman Gopalan. 2013 · 2013
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
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Neural machine translation by jointly learning to align and translate
D. Bahdanau, K. Cho, and Y. Bengio. 2015 · 2015
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Sentence compression by deletion with lstms
Katja Filippova, Enrique Alfonseca, Carlos Colmenares, Lukasz Kaiser, and Oriol Vinyals. 2015 · 2015
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Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2015 · 2015
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A neural attention model for abstractive sentence summarization
Alexander M. Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
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Simultaneous deep transfer across domains and tasks
Eric Tzeng, Judy Hoffman, Trevor Darrell, and Kate Saenko. 2015 · 2015
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Show and tell: A neural image caption generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan. 2015 · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Aaron Courville, Ruslan Salakhutdinov, Richard Zemel, and Yoshua Bengio. 2015 · 2015
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Many languages, one parser
Waleed Ammar, George Mulcaire, Miguel Ballesteros, Chris Dyer, and Noah A. Smith. 2016 · 2016
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Domain separation networks
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, and Dumitru Erhan. 2016 · 2016
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Abstractive sentence summarization with attentive recurrent neural networks
Sumit Chopra, Michael Auli, Alexander M Rush, and SEAS Harvard. 2016 · 2016
Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2016 · 2016
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Bi-transferring deep neural networks for domain adaptation
Guangyou Zhou, Zhiwen Xie, Jimmy Xiangji Huang, and Tingting He. 2016 · 2016
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Deep active learning for dialogue generation
Nabiha Asghar, Pascal Poupart, Xin Jiang, and Hang Li. 2017 · 2017
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A pilot study of domain adaptation effect for neural abstractive summarization
Xinyu Hua and Lu Wang. 2017 · 2017
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Google’s multilingual neural machine translation system: Enabling zero-shot translation
Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda B. Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2016 · 2016
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Frustratingly easy neural domain adaptation
Young-Bum Kim, Karl Stratos, and Ruhi Sarikaya. 2016 · 2016
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Deep reinforcement learning for dialogue generation
Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, and Dan Jurafsky. 2016 · 2016
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Unsupervised domain adaptation with residual transfer networks
Mingsheng Long, Han Zhu, Jianmin Wang, and Michael I Jordan. 2016 · 2016
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Abstractive text summarization using sequence-to-sequence RNNs and beyond
Ramesh Nallapati, Bowen Zhou, Caglar Gulcehre, Bing Xiang, et al. 2016 · 2016
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Learning transferrable representations for unsupervised domain adaptation
Ozan Sener, Hyun Oh Song, Ashutosh Saxena, and Silvio Savarese. 2016 · 2016
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Jiwei Li, Will Monroe, Tianlin Shi, Alan Ritter, and Dan Jurafsky. 2017 · 2017
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Optimization of image description metrics using policy gradient methods
Siqi Liu, Zhenhai Zhu, Ning Ye, Sergio Guadarrama, and Kevin Murphy. 2017 · 2017
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Diversity driven attention model for query-based abstractive summarization
Preksha Nema, Mitesh Khapra, Anirban Laha, and Balaraman Ravindran. 2017 · 2017
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A deep reinforced model for abstractive summarization
Romain Paulus, Caiming Xiong, and Richard Socher. 2017 · 2017
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Multi-task domain adaptation for sequence tagging
Nanyun Peng and Mark Dredze. 2017 · 2017
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J Liu, and Christopher D Manning. 2017 · 2017
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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
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Sentence simplification with deep reinforcement learning
Xingxing Zhang and Mirella Lapata. 2017 · 2017
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