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When writing a summary, humans tend to choose content from one or two sentences and merge them into a single summary sentence.
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Jaime Carbonell and Jade Goldstein. 1998 · 1998
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A noisy-channel model for document compression
Hal Daumé III and Daniel Marcu. 2002 · 2002
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Generic sentence fusion is an ill-defined summarization task
Hal Daumé III and Daniel Marcu. 2004 · 2004
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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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ROUGE: a package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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An introduction to DUC-2004
Paul Over and James Yen. 2004 · 2004
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Sentence fusion for multidocument news summarization
Regina Barzilay and Kathleen R. McKeown. 2005 · 2005
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Multi-document summarization of evaluative text
Giuseppe Carenini, Raymond Ng, and Adam Pauls. 2006 · 2006
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Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
Lucy Vanderwende, Hisami Suzuki, Chris Brockett, and Ani Nenkova. 2007 · 2007
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Multi-candidate reduction: Sentence compression as a tool for document summarization tasks
David Zajic, Bonnie J. Dorr, Jimmy Lin, and Richard Schwartz. 2007 · 2007
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Introduction to Information Retrieval
Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schütze. 2008 · 2008
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Extractive summarization using supervised and semi-supervised learning
Kam-Fai Wong, Mingli Wu, and Wenjie Li. 2008 · 2008
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A scalable global model for summarization
Dan Gillick and Benoit Favre. 2009 · 2009
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Exploring content models for multi-document summarization
Aria Haghighi and Lucy Vanderwende. 2009 · 2009
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Summarization with a joint model for sentence extraction and compression
Andre F. T. Martins and Noah A. Smith. 2009 · 2009
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Multi-sentence compression: Finding shortest paths in word graphs
Katja Filippova. 2010 · 2010
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Opinosis: A graph-based approach to abstractive summarization of highly redundant opinions
Kavita Ganesan, ChengXiang Zhai, and Jiawei Han. 2010 · 2010
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Multi-document summarization via the minimum dominating set
Chao Shen and Tao Li. 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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Learning determinantal point processes
Alex Kulesza and Ben Taskar. 2011 · 2011
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Automatic summarization
Ani Nenkova and Kathleen McKeown. 2011 · 2011
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Extractive multi-document summarization with integer linear programming and support vector regression
Dimitrios Galanis, Gerasimos Lampouras, and Ion Androutsopoulos. 2012 · 2012
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Document summarization via guided sentence compression
Chen Li, Fei Liu, Fuliang Weng, and Yang Liu. 2013 · 2013
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Supervised sentence fusion with single-stage inference
Kapil Thadani and Kathleen McKeown. 2013 · 2013
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A deep reinforced model for abstractive summarization
Romain Paulus, Caiming Xiong, and Richard Socher. 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, Xiaojun Wan, and Jianguo Xiao. 2017 · 2017
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https://arxiv.org/abs/1706.03762
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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A sentence compression based framework to query-focused multi-document summarization
Lu Wang, Hema Raghavan, Vittorio Castelli, Radu Florian, and Claire Cardie. 2013 · 2013
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Improving the estimation of word importance for news multi-document summarization
Kai Hong and Ani Nenkova. 2014 · 2014
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Improving multi-document summarization by sentence compression based on expanded constituent parse tree
Chen Li, Yang Liu, Fei Liu, Lin Zhao, and Fuliang Weng. 2014 · 2014
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Abstractive multi-document summarization via phrase selection and merging
Lidong Bing, Piji Li, Yi Liao, Wai Lam, Weiwei Guo, and Rebecca J. Passonneau. 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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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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Qingyu Zhou, Nan Yang, Furu Wei, and Ming Zhou. 2017 · 2017
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Deep communicating agents for abstractive summarization
Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, and Yejin Choi. 2018 · 2018
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Fast abstractive summarization with reinforce-selected sentence rewriting
Yen-Chun Chen and Mohit Bansal. 2018 · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Bottom-up abstractive summarization
Sebastian Gehrmann, Yuntian Deng, and Alexander M. Rush. 2018 · 2018
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Soft, layer-specific multi-task summarization with entailment and question generation
Han Guo, Ramakanth Pasunuru, and Mohit Bansal. 2018 · 2018
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A unified model for extractive and abstractive summarization using inconsistency loss
Wan-Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, Kerui Min, Jing Tang, and Min Sun. 2018 · 2018
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Content selection in deep learning models of summarization
Chris Kedzie, Kathleen McKeown, and Hal Daume III. 2018 · 2018
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Adapting the neural encoder-decoder framework from single to multi-document summarization
Logan Lebanoff, Kaiqiang Song, and Fei Liu. 2018 · 2018
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Abstract meaning representation for multi-document summarization
Kexin Liao, Logan Lebanoff, and Fei Liu. 2018 · 2018
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Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Structure-infused copy mechanisms for abstractive summarization
Kaiqiang Song, Lin Zhao, and Fei Liu. 2018 · 2018
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Improving the similarity measure of determinantal point processes for extractive multi-document summarization
Sangwoo Cho, Logan Lebanoff, Hassan Foroosh, and Fei Liu. 2019 · 2019
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