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The high annotation costs and diverse demands of various summarization tasks motivate the development of few-shot summarization.
Regularized multi–task learning
Theodoros Evgeniou and Massimiliano Pontil. 2004 · 2004
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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The icsi meeting recorder dialog act (mrda) corpus
Elizabeth Shriberg, Raj Dhillon, Sonali Bhagat, Jeremy Ang, and Hannah Carvey. 2004 · 2004
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The ami meeting corpus
Wessel Kraaij, Thomas Hain, Mike Lincoln, and Wilfried Post. 2005 · 2005
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Sample selection bias correction theory
Corinna Cortes, Mehryar Mohri, Michael Riley, and Afshin Rostamizadeh. 2008 · 2008
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Collective classification in network data
Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Brian Galligher, and Tina Eliassi-Rad. 2008 · 2008
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Jonathan Pilault, Amine Elhattami, and Christopher Pal. 2020 · 2009
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Practical recommendations for gradient-based training of deep architectures
Yoshua Bengio. 2012 · 2012
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Abstractive text summarization using sequence-to-sequence RNNs and beyond
Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Çağlar Gu̇lçehre, and Bing Xiang. 2016 · 2016
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An overview of multi-task learning in deep neural networks
Sebastian Ruder. 2017 · 2017
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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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Wikihow: A large scale text summarization dataset
Mahnaz Koupaee and William Yang Wang. 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. 2018 · 2018
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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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SAMSum corpus: A human-annotated dialogue dataset for abstractive summarization
Bogdan Gliwa, Iwona Mochol, Maciej Biesek, and Aleksander Wawer. 2019 · 2019
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Abstractive summarization of Reddit posts with multi-level memory networks
Byeongchang Kim, Hyunwoo Kim, and Gunhee Kim. 2019 · 2019
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BillSum: A corpus for automatic summarization of US legislation
Anastassia Kornilova and Vladimir Eidelman. 2019 · 2019
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Neural text summarization: A critical evaluation
Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
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Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 2019
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Single document summarization as tree induction
Yang Liu, Ivan Titov, and Mirella Lapata. 2019 · 2019
Cited alongside, same era.
This email could save your life: Introducing the task of email subject line generation
Rui Zhang and Joel Tetreault. 2019 · 2019
Cited alongside, same era.
A closer look at data bias in neural extractive summarization models
Ming Zhong, Danqing Wang, Pengfei Liu, Xipeng Qiu, and Xuan-Jing Huang. 2019 · 2019
Cited alongside, same era.
Few-shot learning for opinion summarization
Arthur Bražinskas, Mirella Lapata, and Ivan Titov. 2020 · 2020
Cited alongside, same era.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Cited alongside, same era.
AdaptSum: Towards low-resource domain adaptation for abstractive summarization
Tiezheng Yu, Zihan Liu, and Pascale Fung. 2021 · 2021
Later among the works it cites.
QMSum: A new benchmark for query-based multi-domain meeting summarization
Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, and Dragomir Radev. 2021 · 2021
Later among the works it cites.
MediaSum: A large-scale media interview dataset for dialogue summarization
Chenguang Zhu, Yang Liu, Jie Mei, and Michael Zeng. 2021 · 2021
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Ext5: Towards extreme multi-task scaling for transfer learning
Vamsi Aribandi, Yi Tay, Tal Schuster, Jinfeng Rao, Huaixiu Steven Zheng, Sanket Vaibhav Mehta, Honglei Zhuang, Vinh Q. Tran, Dara Bahri, Jianmo Ni, Jai Prakash Gupta, Kai Hui, Sebastian Ruder, and Donald Metzler. 2022 · 2022
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From spoken dialogue to formal summary: An utterance rewriting for dialogue summarization
Yue Fang, Hainan Zhang, Hongshen Chen, Zhuoye Ding, Bo Long, Yanyan Lan, and Yanquan Zhou. 2022 · 2022
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Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 2020 · 2020
Cited alongside, same era.
Evaluating the factual consistency of abstractive text summarization
Wojciech Kryscinski, Bryan McCann, Caiming Xiong, and Richard Socher. 2020 · 2020
Cited alongside, same era.
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.
TED: A pretrained unsupervised summarization model with theme modeling and denoising
Ziyi Yang, Chenguang Zhu, Robert Gmyr, Michael Zeng, Xuedong Huang, and Eric Darve. 2020 · 2020
Cited alongside, same era.
PEGASUS: pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter J. Liu. 2020 · 2020
Cited alongside, same era.
Extractive summarization as text matching
Ming Zhong, Pengfei Liu, Yiran Chen, Danqing Wang, Xipeng Qiu, and Xuanjing Huang. 2020 · 2020
Cited alongside, same era.
Cross-lingual abstractive summarization with limited parallel resources
Yu Bai, Yang Gao, and Heyan Huang. 2021 · 2021
Cited alongside, same era.
Discourse-aware soft prompting for text generation
Marjan Ghazvininejad, Vladimir Karpukhin, Vera Gor, and Asli Celikyilmaz. 2022 · 2022
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News summarization and evaluation in the era of gpt-3
Tanya Goyal, Junyi Jessy Li, and Greg Durrett. 2022 · 2022
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PPT: Pre-trained prompt tuning for few-shot learning
Yuxian Gu, Xu Han, Zhiyuan Liu, and Minlie Huang. 2022 · 2022
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Z-code++: A pre-trained language model optimized for abstractive summarization
Pengcheng He, Baolin Peng, Liyang Lu, Song Wang, Jie Mei, Yang Liu, Ruochen Xu, Hany Hassan Awadalla, Yu Shi, Chenguang Zhu, et al. 2022 · 2022
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Learning to transfer prompts for text generation
Junyi Li, Tianyi Tang, Jian-Yun Nie, Ji-Rong Wen, and Xin Zhao. 2022 · 2022
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Cutting down on prompts and parameters: Simple few-shot learning with language models
Robert Logan IV, Ivana Balazevic, Eric Wallace, Fabio Petroni, Sameer Singh, and Sebastian Riedel. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
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Narrate dialogues for better summarization
Ruochen Xu, Chenguang Zhu, and Michael Zeng. 2022 · 2022
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A survey of knowledge-enhanced text generation
Wenhao Yu, Chenguang Zhu, Zaitang Li, Zhiting Hu, Qingyun Wang, Heng Ji, and Meng Jiang. 2022 · 2022
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Macsum: Controllable summarization with mixed attributes
Yusen Zhang, Yang Liu, Ziyi Yang, Yuwei Fang, Yulong Chen, Dragomir Radev, Chenguang Zhu, Michael Zeng, and Rui Zhang. 2022 · 2022
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Dialoglm: Pre-trained model for long dialogue understanding and summarization
Ming Zhong, Yang Liu, Yichong Xu, Chenguang Zhu, and Michael Zeng. 2022a · 2022
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Yiming Wang, Zhuosheng Zhang, and Rui Wang. 2023 · 2023
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Towards a unified multi-dimensional evaluator for text generation
Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji, and Jiawei Han. 2022b · 2038
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