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Single document summarization is the task of producing a shorter version of a document while preserving its principal information content.
Topical coherence for graph-based extractive summarization
Daraksha Parveen, Hans-Martin Ramsl, and Michael Strube. 2015 · 1954
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Rhetorical Structure Theory: Toward a functional theory of text organization
William C. Mann and Sandra A. Thompson. 1988 · 1988
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The effects and limitations of automated text condensing on reading comprehension performance
Andrew H. Morris, George M. Kasper, and Dennis A. Adams. 1992 · 1992
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams. 1992 · 1992
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A trainable document summarizer
Julian Kupiec, Jan Pedersen, and Francine Chen. 1995 · 1995
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Using lexical chains for text summarization
Regina Barzilay and Michael Elhadad. 1997 · 1997
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Long Short-Term Memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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Sentence extraction as a classification task
Simone Teufel and Marc Moens. 1997 · 1997
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The use of MMR, diversity-based reranking for reordering documents and producing summaries
Jaime Carbonell and Jade Goldstein. 1998 · 1998
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Reinforcement Learning : An Introduction
Richard S. Sutton and Andrew G. Barto. 1998 · 1998
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Automatic Summarization
Inderjeet Mani. 2001 · 2001
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SUMMAC: A text summarization evaluation
Inderjeet Mani, Gary Klein, David House, Lynette Hirschman, Therese Firmin, and Beth Sundheim. 2002 · 2002
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Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard Hovy. 2003 · 2003
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LexRank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R. Radev. 2004 · 2004
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Event-based extractive summarization
Elena Filatova and Vasileios Hatzivassiloglou. 2004 · 2004
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TextRank: Bringing order into texts
Rada Mihalcea and Paul Tarau. 2004 · 2004
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MEAD — A platform for multidocument multilingual text summarization
Dragomir Radev, Timothy Allison, Sasha Blair-Goldensohn, John Blitzer, Arda Çelebi, Stanko Dimitrov, Elliott Drabek, Ali Hakim, Wai Lam, Danyu Liu, Jahna Otterbacher, Hong Qi, Horacio Saggion, Simone Teufel, Michael Topper, Adam Winkel, and Zhu Zhang. 2004 · 2004
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A compositional context sensitive multi-document summarizer: Exploring the factors that influence summarization
Ani Nenkova, Lucy Vanderwende, and Kathleen McKeown. 2006 · 2006
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Document summarization using conditional random fields
Dou Shen, Jian-Tao Sun, Hua Li, Qiang Yang, and Zheng Chen. 2007 · 2007
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Automatic summarising: The state of the art
Karen Spärck Jones. 2007 · 2007
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Enhancing single-document summarization by combining ranknet and third-party sources
Krysta Marie Svore, Lucy Vanderwende, and Christopher J. C. Burges. 2007 · 2007
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Multi-document summarization by maximizing informative content-words
Wen-tau Yih, Joshua Goodman, Lucy Vanderwende, and Hisami Suzuki. 2007 · 2007
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FastSum: Fast and accurate query-based multi-document summarization
Frank Schilder and Ravikumar Kondadadi. 2008 · 2008
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Enhancing diversity, coverage and balance for summarization through structure learning
Liangda Li, Ke Zhou, Gui-Rong Xue, Hongyuan Zha, and Yong Yu. 2009 · 2009
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Discourse constraints for document compression
James Clarke and Mirella Lapata. 2010 · 2010
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Towards a unified approach to simultaneous single-document and multi-document summarizations
Xiaojun Wan. 2010 · 2010
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Automatic generation of story highlights
Kristian Woodsend and Mirella Lapata. 2010 · 2010
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Jointly learning to extract and compress
Taylor Berg-Kirkpatrick, Dan Gillick, and Dan Klein. 2011 · 2011
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Natural language processing (almost) from scratch
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011 · 2011
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Automatic summarization
Ani Nenkova and Kathleen McKeown. 2011 · 2011
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A hierarchical neural autoencoder for paragraphs and documents
Jiwei Li, Thang Luong, and Dan Jurafsky. 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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Optimizing sentence modeling and selection for document summarization
Wenpeng Yin and Yulong Pei. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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TGSum: Build tweet guided multi-document summarization dataset
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Framework of automatic text summarization using reinforcement learning
Seonggi Ryang and Takeshi Abekawa. 2012 · 2012
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Multiple aspect summarization using integer linear programming
Kristian Woodsend and Mirella Lapata. 2012 · 2012
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Fast and robust compressive summarization with dual decomposition and multi-task learning
Miguel B. Almeida and André F. T. Martins. 2013 · 2013
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One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
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A convolutional neural network for modelling sentences
Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. 2014 · 2014
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Ziqiang Cao, Chengyao Chen, Wenjie Li, Sujian Li, Furu Wei, and Ming Zhou. 2016 · 2016
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Distraction-based neural networks for modeling documents
Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, and Hui Jiang. 2016 · 2016
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Neural summarization by extracting sentences and words
Jianpeng Cheng and Mirella Lapata. 2016 · 2016
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Character-aware neural language models
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush. 2016 · 2016
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Deep reinforcement learning for dialogue generation
Jiwei Li, Will Monroe, Alan Ritter, Dan Jurafsky, Michel Galley, and Jianfeng Gao. 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
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Minimum risk training for neural machine translation
Shiqi Shen, Yong Cheng, Zhongjun He, Wei He, Hua Wu, Maosong Sun, and Yang Liu. 2016 · 2016
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Towards the use of deep reinforcement learning with global policy for query-based extractive summarisation
Diego Mollá-Aliod. 2017 · 2017
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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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Neural extractive summarization with side information
Shashi Narayan, Nikos Papasarantopoulos, Shay B. Cohen, and Mirella Lapata. 2017 · 2017
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Task-oriented query reformulation with reinforcement learning
Rodrigo Nogueira and Kyunghyun Cho. 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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The limits of automatic summarisation according to rouge
Natalie Schluter. 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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Abstractive document summarization with a graph-based attentional neural model
Jiwei Tan and Xiaojun Wan. 2017 · 2017
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Graph-based neural multi-document summarization
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, and Dragomir Radev. 2017 · 2017
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Sentence simplification with deep reinforcement learning
Xingxing Zhang and Mirella Lapata. 2017 · 2017
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Lei Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhutdinov, Richard S. Zemel, and Yoshua Bengio. 2015 · 2057
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