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Pre-trained language models (PLMs) have achieved outstanding achievements in abstractive single-document summarization (SDS).
Information fusion in the context of multi-document summarization
Regina Barzilay, Kathleen McKeown, and Michael Elhadad. 1999 · 1999
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Catastrophic forgetting in connectionist networks
Robert M French. 1999 · 1999
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Dyne: Dynamic ensemble decoding for multi-document summarization
Chris Hokamp, Demian Gholipour Ghalandari, Nghia The Pham, and John Glover. 2020a · 2006
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Dyne: Dynamic ensemble decoding for multi-document summarization
Chris Hokamp, Demian Gholipour Ghalandari, Nghia The Pham, and John Glover. 2020b · 2006
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Opinosis: A graph based approach to abstractive summarization of highly redundant opinions
Kavita A. Ganesan, ChengXiang Zhai, and Jiawei Han. 2010 · 2010
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Towards coherent multi-document summarization
Janara Christensen, Stephen Soderland, Oren Etzioni, et al. 2013 · 2013
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Multi-document summarization using bipartite graphs
Daraksha Parveen and Michael Strube. 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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Neural network-based abstract generation for opinions and arguments
Lu Wang and Wang Ling. 2016 · 2016
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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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Graph-based neural multi-document summarization
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishna Parasuram Srinivasan, and Dragomir R. Radev. 2017 · 2017
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Tal Baumel, Matan Eyal, and Michael Elhadad. 2018 · 2018
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Meansum: A neural model for unsupervised multi-document abstractive summarization
Eric Chu and Peter J. Liu. 2018 · 2018
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A discourse-aware attention model for abstractive summarization of long documents
Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian. 2018 · 2018
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Bottom-up abstractive summarization
Sebastian Gehrmann, Yuntian Deng, and Alexander M Rush. 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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Actor-critic based training framework for abstractive summarization
Piji Li, Lidong Bing, and Wai Lam. 2018 · 2018
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Generating wikipedia by summarizing long sequences
Peter J Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
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Informative and controllable opinion summarization
Reinald Kim Amplayo and Mirella Lapata. 2019 · 2019
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Scibert: A pretrained language model for scientific text
Iz Beltagy, Kyle Lo, and Arman Cohan. 2019 · 2019
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Sgsum: Transforming multi-document summarization into sub-graph selection
Moye Chen, Wei Li, Jiachen Liu, Xinyan Xiao, Hua Wu, and Haifeng Wang. 2021 · 2021
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Topic-guided abstractive multi-document summarization
Peng Cui and Le Hu. 2021 · 2021
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Wikiasp: A dataset for multi-domain aspect-based summarization
Hiroaki Hayashi, Prashant Budania, Peng Wang, Chris Ackerson, Raj Neervannan, and Graham Neubig. 2021 · 2021
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Efficient attentions for long document summarization
Luyang Huang, Shuyang Cao, Nikolaus Parulian, Heng Ji, and Lu Wang. 2021 · 2021
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Highlight-transformer: Leveraging key phrase aware attention to improve abstractive multi-document summarization
Shuaiqi Liu, Jiannong Cao, Ruosong Yang, and Zhiyuan Wen. 2021 · 2021
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Efficiently summarizing text and graph encodings of multi-document clusters
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Alexander Richard Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir Radev. 2019 · 2019
Cited alongside, same era.
BIGPATENT: A large-scale dataset for abstractive and coherent summarization
Eva Sharma, Chen Li, and Lu Wang. 2019 · 2019
Cited alongside, same era.
Unsupervised opinion summarization with content planning
Reinald Kim Amplayo, Stefanos Angelidis, and Mirella Lapata. 2020 · 2020
Cited alongside, same era.
Unsupervised opinion summarization with noising and denoising
Reinald Kim Amplayo and Mirella Lapata. 2020 · 2020
Cited alongside, same era.
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 · 2020
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Generating representative headlines for news stories
Xiaotao Gu, Yuning Mao, Jiawei Han, Jialu Liu, You Wu, Cong Yu, Daniel Finnie, Hongkun Yu, Jiaqi Zhai, and Nicholas Zukoski. 2020 · 2020
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
Ramakanth Pasunuru, Mengwen Liu, Mohit Bansal, Sujith Ravi, and Markus Dreyer. 2021 · 2021
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Multi-document summarization with determinantal point process attention
Laura Perez-Beltrachini and Mirella Lapata. 2021 · 2021
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Entity-aware abstractive multi-document summarization
Hao Zhou, Weidong Ren, Gongshen Liu, Bo Su, and Wei Lu. 2021 · 2021
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Proposition-level clustering for multi-document summarization
Ori Ernst, Avi Caciularu, Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Jacob Goldberger, and Ido Dagan. 2022 · 2022
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LongT5: Efficient text-to-text transformer for long sequences
Mandy Guo, Joshua Ainslie, David Uthus, Santiago Ontanon, Jianmo Ni, Yun-Hsuan Sung, and Yinfei Yang. 2022 · 2022
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SummaC: Re-visiting NLI-based models for inconsistency detection in summarization
Philippe Laban, Tobias Schnabel, Paul N. Bennett, and Marti A. Hearst. 2022 · 2022
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Leveraging locality in abstractive text summarization
Yixin Liu, Ansong Ni, Linyong Nan, Budhaditya Deb, Chenguang Zhu, Ahmed H Awadallah, and Dragomir Radev. 2022 · 2022
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Multi-document summarization with centroid-based pretraining
Ratish Puduppully and Mark Steedman. 2022 · 2022
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Improving multi-document summarization through referenced flexible extraction with credit-awareness
Yun-Zhu Song, Yi-Syuan Chen, and Hong-Han Shuai. 2022 · 2022
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UPER: Boosting multi-document summarization with an unsupervised prompt-based extractor
Shangqing Tu, Jifan Yu, Fangwei Zhu, Juanzi Li, Lei Hou, and Jian-Yun Nie. 2022 · 2022
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How “multi” is multi-document summarization?
Ruben Wolhandler, Arie Cattan, Ori Ernst, and Ido Dagan. 2022 · 2022
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Primera: Pyramid-based masked sentence pre-training for multi-document summarization
Wen Xiao, Iz Beltagy, Giuseppe Carenini, and Arman Cohan. 2022 · 2022
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