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Abstractive text summarization aims at compressing the information of a long source document into a rephrased, condensed summary.
Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 1908
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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On the shortest arborescence of a directed graph
Yau Chu and Tung Kuan Liu. 1965 · 1965
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Optimum branchings
Jack Edmonds. 1967 · 1967
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Graph theory, vol. 21 of
William Thomas Tutte. 1984 · 1984
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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Hedge trimmer: A parse-and-trim approach to headline generation
Bonnie Dorr, David Zajic, and Richard Schwartz. 2003 · 2003
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Neural abstractive summarization with structural attention
Tanya Chowdhury, Sachin Kumar, and Tanmoy Chakraborty. 2020 · 2004
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Learning sub-structures of document semantic graphs for document summarization
Jure Leskovec, Marko Grobelnik, and Natasa Milic-Frayling. 2004 · 2004
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Generating soap notes from doctor-patient conversations
Kundan Krishna, Sopan Khosla, Jeffrey P Bigham, and Zachary C Lipton. 2020 · 2005
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Learning-based single-document summarization with compression and anaphoricity constraints
Greg Durrett, Taylor Berg-Kirkpatrick, and Dan Klein. 2016 · 2008
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Graph-based keyword extraction for single-document summarization
Marina Litvak and Mark Last. 2008 · 2008
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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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Discourse structures to reduce discourse incoherence in blog summarization
Shamima Mithun and Leila Kosseim. 2011 · 2011
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Single document summarization based on nested tree structure
Yuta Kikuchi, Tsutomu Hirao, Hiroya Takamura, Manabu Okumura, and Masaaki Nagata. 2014 · 2014
Cited alongside, same era.
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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Toward abstractive summarization using semantic representations
Fei Liu, Jeffrey Flanigan, Sam Thomson, Norman Sadeh, and Noah A. Smith. 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.
Long short-term memory-networks for machine reading
Jianpeng Cheng, Li Dong, and Mirella Lapata. 2016 · 2016
Cited alongside, same era.
Abstractive text summarization using sequence-to-sequence RNNs and beyond
Bottom-up abstractive summarization
Sebastian Gehrmann, Yuntian Deng, and Alexander M. Rush. 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 Daumé III. 2018 · 2018
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Improving neural abstractive document summarization with structural regularization
Wei Li, Xinyan Xiao, Yajuan Lyu, and Yuanzhuo Wang. 2018 · 2018
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Çağlar Gu̇lçehre, and Bing Xiang. 2016 · 2016
Cited alongside, same era.
Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alexander J. Smola, and Eduard H. Hovy. 2016 · 2016
Cited alongside, same era.
Structured attention networks
Yoon Kim, Carl Denton, Luong Hoang, and Alexander M. Rush. 2017 · 2017
Cited alongside, same era.
Learning structured text representations
Yang Liu and Mirella Lapata. 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
Cited alongside, same era.
Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
Cited alongside, same era.
Abstractive document summarization with a graph-based attentional neural model
Jiwei Tan, Xiaojun Wan, and Jianguo Xiao. 2017 · 2017
Cited alongside, same era.
Pengjie Ren, Zhumin Chen, Zhaochun Ren, Furu Wei, Liqiang Nie, Jun Ma, and Maarten De Rijke. 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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Neural latent extractive document summarization
Xingxing Zhang, Mirella Lapata, Furu Wei, and Ming Zhou. 2018 · 2018
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Evaluating discourse in structured text representations
Elisa Ferracane, Greg Durrett, Junyi Jessy Li, and Katrin Erk. 2019 · 2019
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Inducing document structure for aspect-based summarization
Lea Frermann and Alexandre Klementiev. 2019 · 2019
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Unsupervised neural single-document summarization of reviews via learning latent discourse structure and its ranking
Masaru Isonuma, Junichiro Mori, and Ichiro Sakata. 2019 · 2019
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Neural text summarization: A critical evaluation
Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
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Abstractive summarization: A survey of the state of the art
Hui Lin and Vincent Ng. 2019 · 2019
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Topic-aware pointer-generator networks for summarizing spoken conversations
Zhengyuan Liu, Angela Ng, Sheldon Lee Shao Guang, AiTi Aw, and Nancy F. Chen. 2019 · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, V. Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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