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Neural sequence-to-sequence models have provided a viable new approach for abstractive text summarization (meaning they are not restricted to simply selecting and rearranging passages from the original text).
Constructing literature abstracts by computer: techniques and prospects
Chris D Paice. 1990 · 1990
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A trainable document summarizer
Julian Kupiec, Jan Pedersen, and Francine Chen. 1995 · 1995
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Sentence reduction for automatic text summarization
Hongyan Jing. 2000 · 2000
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Statistical machine translation
Philipp Koehn. 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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Automatic text summarization: Past, present and future
Horacio Saggion and Thierry Poibeau. 2013 · 2013
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Unsupervised sentence enhancement for automatic summarization
Jackie Chi Kit Cheung and Gerald Penn. 2014 · 2014
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Meteor universal: Language specific translation evaluation for any target language
Michael Denkowski and Alon Lavie. 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
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Cited alongside, same era.
A neural attention model for abstractive sentence summarization
Alexander M Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
Cited alongside, same era.
Pointer networks
Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly. 2015 · 2015
Cited alongside, same era.
Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C Courville, Ruslan Salakhutdinov, Richard S Zemel, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
Distraction-based neural networks for modeling documents
Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, and Hui Jiang. 2016 · 2016
Cited alongside, same era.
Abstractive sentence summarization with attentive recurrent neural networks
Sumit Chopra, Michael Auli, and Alexander M Rush. 2016 · 2016
Language as a latent variable: Discrete generative models for sentence compression
Yishu Miao and Phil Blunsom. 2016 · 2016
Later among the works it cites.
Abstractive text summarization using sequence-to-sequence RNNs and beyond
Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Çaglar Gulçehre, and Bing Xiang. 2016 · 2016
Later among the works it cites.
Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2016 · 2016
Later among the works it cites.
Temporal attention model for neural machine translation
Baskaran Sankaran, Haitao Mi, Yaser Al-Onaizan, and Abe Ittycheriah. 2016 · 2016
Later among the works it cites.
RNN-based encoder-decoder approach with word frequency estimation
Jun Suzuki and Masaaki Nagata. 2016 · 2016
Later among the works it cites.
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Cited alongside, same era.
Incorporating copying mechanism in sequence-to-sequence learning
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor OK Li. 2016 · 2016
Cited alongside, same era.
Pointing the unknown words
Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, and Yoshua Bengio. 2016 · 2016
Cited alongside, same era.
Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2016 · 2016
Cited alongside, same era.
Coverage embedding models for neural machine translation
Haitao Mi, Baskaran Sankaran, Zhiguo Wang, and Abe Ittycheriah. 2016 · 2016
Cited alongside, same era.
Looking for a few good metrics: Automatic summarization evaluation-how many samples are enough?
Chin-Yew Lin. 2004a
Cited in the paper.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004b
Cited in the paper.
Neural headline generation on abstract meaning representation
Sho Takase, Jun Suzuki, Naoaki Okazaki, Tsutomu Hirao, and Masaaki Nagata. 2016 · 2016
Later among the works it cites.
Modeling coverage for neural machine translation
Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, and Hang Li. 2016 · 2016
Later among the works it cites.
Efficient summarization with read-again and copy mechanism
Wenyuan Zeng, Wenjie Luo, Sanja Fidler, and Raquel Urtasun. 2016 · 2016
Later among the works it cites.
SummaRuNNer: A recurrent neural network based sequence model for extractive summarization of documents
Ramesh Nallapati, Feifei Zhai, and Bowen Zhou. 2017 · 2017
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