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Single document summarization has enjoyed renewed interests in recent years thanks to the popularity of neural network models and the availability of large-scale datasets.
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Learning-based single-document summarization with compression and anaphoricity constraints
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The pagetrust algorithm: How to rank web pages when negative links are allowed?
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Fastsum: Fast and accurate query-based multi-document summarization
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An exploration of document impact on graph-based multi-document summarization
Xiaojun Wan. 2008 · 2008
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Multi-document summarization using cluster-based link analysis
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Discourse constraints for document compression
James Clarke and Mirella Lapata. 2010 · 2010
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A study on position information in document summarization
You Ouyang, Wenjie Li, Qin Lu, and Renxian Zhang. 2010 · 2010
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Automatic summarization
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Discourse parsing with attention-based hierarchical neural networks
Qi Li, Tianshi Li, and Baobao Chang. 2016 · 2016
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Abstractive text summarization using sequence-to-sequence rnns and beyond
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Overview of the nlpcc 2017 shared task: Single document summarization
Lifeng Hua, Xiaojun Wan, and Lei Li. 2017 · 2017
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Salience estimation via variational auto-encoders for multi-document summarization
Piji Li, Zihao Wang, Wai Lam, Zhaochun Ren, and Lidong Bing. 2017 · 2017
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Learning contextually informed representations for linear-time discourse parsing
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Single-document summarization as a tree knapsack problem
Tsutomu Hirao, Yasuhisa Yoshida, Masaaki Nishino, Norihito Yasuda, and Masaaki Nagata. 2013 · 2013
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Combining intra- and multi-sentential rhetorical parsing for document-level discourse analysis
Shafiq Joty, Giuseppe Carenini, Raymond Ng, and Yashar Mehdad. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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A linear-time bottom-up discourse parser with constraints and post-editing
Vanessa Wei Feng and Graeme Hirst. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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Yang Liu and Mirella Lapata. 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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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Unsupervised neural multi-document abstractive summarization
Eric Chu and Peter J. Liu. 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 Rush. 2018 · 2018
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NEWSROOM: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 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. 2018a · 2018
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Ranking sentences for extractive summarization with reinforcement learning
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018b · 2018
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A deep reinforced model for abstractive summarization
Romain Paulus, Caiming Xiong, and Richard Socher. 2018 · 2018
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