Fetching the paper…
Reading the bibliography…
Attention-based neural abstractive summarization systems equipped with copy mechanisms have shown promising results.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
The meteor metric for automatic evaluation of machine translation
Alon Lavie and Michael J Denkowski. 2009 · 2009
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Earlier work this paper cites.
A neural attention model for abstractive sentence summarization
Alexander M Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
Cited alongside, same era.
Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, and Yoshua Bengio. 2016 · 2016
Cited alongside, same era.
A simple, fast diverse decoding algorithm for neural generation
Jiwei Li, Will Monroe, and Dan Jurafsky. 2016 · 2016
Cited alongside, same era.
Learning to decode for future success
Jiwei Li, Will Monroe, and Dan Jurafsky. 2017 · 2017
Cited alongside, same era.
Trainable greedy decoding for neural machine translation
Jiatao Gu, Kyunghyun Cho, and Victor OK Li. 2017a
Cited in the paper.
Incorporating copying mechanism in sequence-to-sequence learning
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor OK Li. 2016a
Cited in the paper.
Learning to translate in real-time with neural machine translation
Jiatao Gu, Graham Neubig, Kyunghyun Cho, and Victor OK Li. 2016b
Cited in the paper.
Search engine guided non-parametric neural machine translation
Jiatao Gu, Yong Wang, Kyunghyun Cho, and Victor OK Li. 2017b
Cited in the paper.
Ramesh Nallapati, Feifei Zhai, and Bowen Zhou. 2016a
Cited in the paper.
Abstractive text summarization using sequence-to-sequence rnns and beyond
Ramesh Nallapati, Bowen Zhou, Cícero Nogueira dos Santos, Çaglar Gülcehre, and Bing Xiang. 2016b
Cited in the paper.
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.
Challenges in data-to-document generation
Sam Wiseman, Stuart M Shieber, and Alexander M Rush. 2017 · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…