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In a world of proliferating data, the ability to rapidly summarize text is growing in importance.
English gigaword
David Graff, Junbo Kong, Ke Chen, and Kazuaki Maeda. 2003 · 2003
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Bbn/umd at duc-2004: Topiary
David Zajic, Bonnie Dorr, and Richard Schwartz. 2004 · 2004
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Moses: Open source toolkit for statistical machine translation
Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, et al. 2007 · 2007
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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Rouge 2.0: Updated and improved measures for evaluation of summarization tasks
Kavita Ganesan. 2015 · 2015
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From word embeddings to document distances
Matt Kusner, Yu Sun, Nicholas Kolkin, and Kilian Weinberger. 2015 · 2015
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A neural attention model for abstractive sentence summarization
Alexander M Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
Cited alongside, same era.
Abstractive sentence summarization with attentive recurrent neural networks
Sumit Chopra, Michael Auli, and Alexander M Rush. 2016 · 2016
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Abstractive text summarization using sequence-to-sequence rnns and beyond
Ramesh Nallapati, Bowen Zhou, Cícero Nogueira dos Santos, Çaglar Gülçehre, and Bing Xiang. 2016 · 2016
Cited alongside, same era.
Efficient summarization with read-again and copy mechanism
Wenyuan Zeng, Wenjie Luo, Sanja Fidler, and Raquel Urtasun. 2016 · 2016
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loic Barrault, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Summarunner: A recurrent neural network based sequence model for extractive summarization of documents
Ramesh Nallapati, Feifei Zhai, and Bowen Zhou. 2017 · 2017
Later among the works it cites.
A deep reinforced model for abstractive summarization
Romain Paulus, Caiming Xiong, and Richard Socher. 2017 · 2017
Later among the works it cites.
Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 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, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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A survey on neural network-based summarization methods
Yue Dong. 2018 · 2018
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Recent automatic text summarization techniques: a survey
Mahak Gambhir and Vishal Gupta. 2017 · 2017
Cited alongside, same era.
Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N Dauphin. 2017 · 2017
Cited alongside, same era.
Piji Li, Lidong Bing, and Wai Lam. 2018 · 2018
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Generating wikipedia by summarizing long sequences
Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
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