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Neural attention models have achieved significant improvements on many natural language processing tasks.
On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
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On the intrinsic locality properties of web reference streams
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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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Sentence fusion for multidocument news summarization
Regina Barzilay and Kathleen R. McKeown. 2005 · 2005
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The locality principle
Peter J. Denning. 2005 · 2005
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Linformer: Self-attention with linear complexity
Sinong Wang, Belinda Z. Li, Madian Khabsa, Han Fang, and Hao Ma. 2020 · 2006
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Seal: Segment-wise extractive-abstractive long-form text summarization
Yao Zhao, Mohammad Saleh, and Peter J. Liu. 2020 · 2006
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Computing krippendorff’s alpha-reliability
Klaus Krippendorff. 2011 · 2011
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An introduction to syntactic analysis and theory
Hilda Koopman, Dominique Sportiche, and Edward Stabler. 2013 · 2013
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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A neural attention model for abstractive sentence summarization
Alexander M. Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
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Locality-aware partitioning in parallel database systems
Erfan Zamanian, Carsten Binnig, and Abdallah Salama. 2015 · 2015
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Abstractive text summarization using sequence-to-sequence RNNs and beyond
Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Çağlar Gulçehre, and Bing Xiang. 2016 · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Rethinking the inception architecture for computer vision
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna. 2016 · 2016
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Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016
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Coarse-to-fine attention models for document summarization
Jeffrey Ling and Alexander Rush. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Fast abstractive summarization with reinforce-selected sentence rewriting
Yen-Chun Chen and Mohit Bansal. 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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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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Adapting neural single-document summarization model for abstractive multi-document summarization: A pilot study
Jianmin Zhang, Jiwei Tan, and Xiaojun Wan. 2018 · 2018
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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Unsupervised extractive summarization by pre-training hierarchical transformers
Shusheng Xu, Xingxing Zhang, Yi Wu, Furu Wei, and Ming Zhou. 2020b · 2020
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Big bird: Transformers for longer sequences
Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, and Amr Ahmed. 2020 · 2020
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Pegasus: Pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter Liu. 2020 · 2020
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Rethinking attention with performers
Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J Colwell, and Adrian Weller. 2021 · 2021
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
Alexander Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir Radev. 2019 · 2019
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Structured neural summarization
Patrick Fernandes, Miltiadis Allamanis, and Marc Brockschmidt. 2019 · 2019
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Hierarchical transformers for multi-document summarization
Yang Liu and Mirella Lapata. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Extractive summarization of long documents by combining global and local context
Wen Xiao and Giuseppe Carenini. 2019 · 2019
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Neural extractive text summarization with syntactic compression
Jiacheng Xu and Greg Durrett. 2019 · 2019
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Discourse-aware unsupervised summarization for long scientific documents
Yue Dong, Andrei Mircea, and Jackie Chi Kit Cheung. 2021 · 2021
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A proposition-level clustering approach for multi-document summarization
Ori Ernst, Avi Caciularu, Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Jacob Goldberger, and Ido Dagan. 2021 · 2021
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SummEval: Re-evaluating Summarization Evaluation
Alexander R. Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021 · 2021
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SimCSE: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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Longt5: Efficient text-to-text transformer for long sequences
Mandy Guo, Joshua Ainslie, David C. Uthus, Santiago Ontañón, Jianmo Ni, Yun-Hsuan Sung, and Yinfei Yang. 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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Long-span summarization via local attention and content selection
Potsawee Manakul and Mark Gales. 2021 · 2021
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Efficiently summarizing text and graph encodings of multi-document clusters
Ramakanth Pasunuru, Mengwen Liu, Mohit Bansal, Sujith Ravi, and Markus Dreyer. 2021 · 2021
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Random feature attention
Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah Smith, and Lingpeng Kong. 2021 · 2021
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Hierarchical learning for generation with long source sequences
Tobias Rohde, Xiaoxia Wu, and Yinhan Liu. 2021 · 2021
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HIBRIDS: Attention with hierarchical biases for structure-aware long document summarization
Shuyang Cao and Lu Wang. 2022 · 2022
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Snac: Coherence error detection for narrative summarization
Tanya Goyal, Junyi Jessy Li, and Greg Durrett. 2022 · 2022
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DYLE: Dynamic latent extraction for abstractive long-input summarization
Ziming Mao, Chen Henry Wu, Ansong Ni, Yusen Zhang, Rui Zhang, Tao Yu, Budhaditya Deb, Chenguang Zhu, Ahmed Awadallah, and Dragomir Radev. 2022 · 2022
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HiStruct+: Improving extractive text summarization with hierarchical structure information
Qian Ruan, Malte Ostendorff, and Georg Rehm. 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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