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Multi-document summarization (MDS) aims to compress the content in large document collections into short summaries and has important applications in story clustering for newsfeeds, presentation of search results, and timeline generation.
ROUGE: A Package for Automatic Evaluation of Summaries. In Text Summarization Branches Out . Association for Computational Linguistics, Barcelona, Spain, 74–81
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Textrank: Bringing order into text. In Proceedings of the 2004 conference on empirical methods in natural language processing . 404–411
Rada Mihalcea and Paul Tarau. 2004 · 2004
Earlier work this paper cites.
An introduction to duc-2004. In Proceedings of the 4th Document Understanding Conference (DUC 2004)
Over Paul and Yen James. 2004 · 2004
Earlier work this paper cites.
Centroid-based summarization of multiple documents
Dragomir R Radev, Hongyan Jing, Małgorzata Styś, and Daniel Tam. 2004 · 2004
Earlier work this paper cites.
A scalable global model for summarization. In Proceedings of the Workshop on Integer Linear Programming for Natural Langauge Processing . Association for Computational Linguistics, 10–18
Dan Gillick and Benoit Favre. 2009 · 2009
Earlier work this paper cites.
Opinosis: A graph based approach to abstractive summarization of highly redundant opinions. In Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010) . 340–348
Kavita Ganesan, ChengXiang Zhai, and Jiawei Han. 2010 · 2010
Earlier work this paper cites.
A class of submodular functions for document summarization. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Volume 1 . Association for Computational Linguistics, 510–520
Hui Lin and Jeff Bilmes. 2011 · 2011
Earlier work this paper cites.
Overview of the TAC 2011 summarization track: Guided task and AESOP task. In Proceedings of the Text Analysis Conference (TAC 2011), Gaithersburg, Maryland, USA, November
Karolina Owczarzak and Hoa Trang Dang. 2011 · 2011
Earlier work this paper cites.
Improving the estimation of word importance for news multi-document summarization. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics . 712–721
Kai Hong and Ani Nenkova. 2014 · 2014
Earlier work this paper cites.
Multi-document abstractive summarization using ILP based multi-sentence compression. In Proceedings of the 24th International Conference on Artificial Intelligence . AAAI Press, 1208–1214
Siddhartha Banerjee, Prasenjit Mitra, and Kazunari Sugiyama. 2015 · 2015
Earlier work this paper cites.
Ranking with recursive neural networks and its application to multi-document summarization. In Twenty-ninth AAAI conference on artificial intelligence
Ziqiang Cao, Furu Wei, Li Dong, Sujian Li, and Ming Zhou. 2015 · 2015
Cited alongside, same era.
A Neural Attention Model for Abstractive Sentence Summarization. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing . 379–389
Alexander M Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
Cited alongside, same era.
Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond. In Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning . 280–290
Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Caglar Gulcehre, and Bing Xiang. 2016 · 2016
Cited alongside, same era.
A general optimization framework for multi-document summarization using genetic algorithms and swarm intelligence. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers . 247–257
Maxime Peyrard and Judith Eckle-Kohler. 2016 · 2016
Cited alongside, same era.
Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) . 708–719
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
Later among the works it cites.
Generating Wikipedia by Summarizing Long Sequences. In International Conference on Learning Representations
Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
Later among the works it cites.
Abstractive unsupervised multi-document summarization using paraphrastic sentence fusion. In Proceedings of the 27th International Conference on Computational Linguistics . 1191–1204
Mir Tafseer Nayeem, Tanvir Ahmed Fuad, and Yllias Chali. 2018 · 2018
Later among the works it cites.
A Deep Reinforced Model for Abstractive Summarization. In International Conference on Learning Representations
Romain Paulus, Caiming Xiong, and Richard Socher. 2018 · 2018
Later among the works it cites.
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A Redundancy-Aware Sentence Regression Framework for Extractive Summarization. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers . The COLING 2016 Organizing Committee, Osaka, Japan, 33–43
Pengjie Ren, Furu Wei, Zhumin Chen, Jun Ma, and Ming Zhou. 2016 · 2016
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.
Get To The Point: Summarization with Pointer-Generator Networks. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 1073–1083
Abigail See, Peter J Liu, and Christopher D Manning. 2017 · 2017
Cited alongside, same era.
Attention is all you need. In Advances in neural information processing systems . 5998–6008
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Graph-based Neural Multi-Document Summarization. In Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017) . 452–462
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, and Dragomir Radev. 2017 · 2017
Cited alongside, same era.
Bottom-Up Abstractive Summarization. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . 4098–4109
Sebastian Gehrmann, Yuntian Deng, and Alexander M Rush. 2018 · 2018
Cited alongside, same era.
Jianmin Zhang, Jiwei Tan, and Xiaojun Wan. 2018 · 2018
Later among the works it cites.
Auto-hMDS: Automatic Construction of a Large Heterogeneous Multilingual Multi-Document Summarization Corpus. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
Markus Zopf. 2018 · 2018
Later among the works it cites.
Which Scores to Predict in Sentence Regression for Text Summarization?. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) . 1782–1791
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. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) . 4171–4186
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. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28- August 2, 2019, Volume 1: Long Papers . 1074–1084
Alexander Richard Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir R. Radev. 2019 · 2019
Later among the works it cites.