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Sequence-to-sequence (s2s) models are the basis for extensive work in natural language processing.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R’emi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
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Multi-document summarization by sentence extraction
Jade Goldstein, Vibhu Mittal, Jaime Carbonell, and Mark Kantrowitz. 2000 · 2000
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Self-supervised and controlled multi-document opinion summarization
Hady ElSahar, Maximin Coavoux, Matthias Gallé, and Jos Rozen. 2020 · 2004
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An introduction to duc-2004
Over Paul and Yen James. 2004 · 2004
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Centroid-based summarization of multiple documents
Dragomir R Radev, Hongyan Jing, Małgorzata Styś, and Daniel Tam. 2004 · 2004
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A large-scale multi-document summarization dataset from the wikipedia current events portal
Demian Gholipour Ghalandari, Chris Hokamp, Nghia The Pham, John Glover, and Georgiana Ifrim. 2020 · 2005
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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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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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Jointly learning to extract and compress
Taylor Berg-Kirkpatrick, Dan Gillick, and Dan Klein. 2011 · 2011
Cited alongside, same era.
A class of submodular functions for document summarization
Hui Lin and Jeff Bilmes. 2011 · 2011
Cited alongside, same era.
Overview of the tac 2011 summarization track: Guided task and aesop task
Karolina Owczarzak and Hoa Trang Dang. 2011 · 2011
Cited alongside, same era.
Improving the estimation of word importance for news multi-document summarization
Kai Hong and Ani Nenkova. 2014 · 2014
Cited alongside, same era.
Multi-document abstractive summarization using ilp based multi-sentence compression
Siddhartha Banerjee, Prasenjit Mitra, and Kazunari Sugiyama. 2015 · 2015
Cited alongside, same era.
Abstractive text summarization using sequence-to-sequence RNNs and beyond
Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Çağlar Gu̇lçehre, and Bing Xiang. 2016 · 2016
Abstractive unsupervised multi-document summarization using paraphrastic sentence fusion
Mir Tafseer Nayeem, Tanvir Ahmed Fuad, and Yllias Chali. 2018 · 2018
Later among the works it cites.
Auto-hmds: Automatic construction of a large heterogeneous multilingual multi-document summarization corpus
Markus Zopf. 2018 · 2018
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Which scores to predict in sentence regression for text summarization?
Markus Zopf, Eneldo Loza Mencía, and Johannes Fürnkranz. 2018 · 2018
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Later among the works it cites.
Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
Alexander Richard Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir R. Radev. 2019 · 2019
Later among the works it cites.
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Cited alongside, same era.
Towards abstractive multi-document summarization using submodular function-based framework, sentence compression and merging
Yllias Chali, Moin Tanvee, and Mir Tafseer Nayeem. 2017 · 2017
Cited alongside, same era.
Graph-based neural multi-document summarization
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, and Dragomir Radev. 2017 · 2017
Cited alongside, same era.
Adapting the neural encoder-decoder framework from single to multi-document summarization
Logan Lebanoff, Kaiqiang Song, and Fei Liu. 2018 · 2018
Cited alongside, same era.
Generating wikipedia by summarizing long sequences
Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
Cited alongside, same era.
Cross-lingual language model pretraining
Guillaume Lample and Alexis Conneau. 2019 · 2019
Later among the works it cites.
Hierarchical transformers for multi-document summarization
Yang Liu and Mirella Lapata. 2019 · 2019
Later among the works it cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019 · 2019
Later among the works it cites.
ELECTRA: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
Closest in time.
Generating Representative Headlines for News Stories
Xiaotao Gu, Yuning Mao, Jiawei Han, Jialu Liu, Hongkun Yu, You Wu, Cong Yu, Daniel Finnie, Jiaqi Zhai, and Nicholas Zukoski. 2020 · 2020
Closest in time.