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Existing summarization systems mostly generate summaries purely relying on the content of the source document.
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
Earlier work this paper cites.
Shen Gao, Xiuying Chen, Piji Li, Zhangming Chan, Dongyan Zhao, and Rui Yan. 2019 · 1909
Earlier work this paper cites.
Billsum: A corpus for automatic summarization of US legislation
Anastassia Kornilova and Vlad Eidelman. 2019 · 1910
Earlier work this paper cites.
Evaluating the factual consistency of abstractive text summarization
Wojciech Kryściński, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 1910
Earlier work this paper cites.
Abstractive summarization with combination of pre-trained sequence-to-sequence and saliency models
Itsumi Saito, Kyosuke Nishida, Kosuke Nishida, and Junji Tomita. 2020 · 2003
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
The ami meeting corpus
Iain McCowan, Jean Carletta, Wessel Kraaij, Simone Ashby, S Bourban, M Flynn, M Guillemot, Thomas Hain, J Kadlec, Vasilis Karaiskos, et al. 2005 · 2005
Earlier work this paper cites.
Gsum: A general framework for guided neural abstractive summarization
Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, Zhengbao Jiang, and Graham Neubig. 2020 · 2010
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
A template-based abstractive meeting summarization: Leveraging summary and source text relationships
Tatsuro Oya, Yashar Mehdad, Giuseppe Carenini, and Raymond Ng. 2014 · 2014
Earlier work this paper cites.
Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Earlier work this paper cites.
Abstractive text summarization using sequence-to-sequence rnns and beyond
Ramesh Nallapati, Bowen Zhou, Caglar Gulcehre, Bing Xiang, et al. 2016 · 2016
Earlier work this paper cites.
Summarunner: A recurrent neural network based sequence model for extractive summarization of documents
Ramesh Nallapati, Feifei Zhai, and Bowen Zhou. 2017 · 2017
Cited alongside, same era.
Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J Liu, and Christopher D Manning. 2017 · 2017
Cited alongside, same era.
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
Cited alongside, same era.
Retrieve, rerank and rewrite: Soft template based neural summarization
Ziqiang Cao, Wenjie Li, Sujian Li, and Furu Wei. 2018 · 2018
Cited alongside, same era.
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
Cited alongside, same era.
Searching for effective neural extractive summarization: What works and what’s next
Ming Zhong, Pengfei Liu, Danqing Wang, Xipeng Qiu, and Xuan-Jing Huang. 2019 · 2019
Later among the works it cites.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross B. Girshick. 2020 · 2020
Later among the works it cites.
Knowledge graph-augmented abstractive summarization with semantic-driven cloze reward
Luyang Huang, Lingfei Wu, and Lu Wang. 2020 · 2020
Later among the works it cites.
Semsum: Semantic dependency guided neural abstractive summarization
Hanqi Jin, Tianming Wang, and Xiaojun Wan. 2020 · 2020
Later among the works it cites.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
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Chenliang Li, Weiran Xu, Si Li, and Sheng Gao. 2018 · 2018
Cited alongside, same era.
Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter. 2018 · 2018
Cited alongside, same era.
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
Cited alongside, same era.
Unsupervised abstractive meeting summarization with multi-sentence compression and budgeted submodular maximization
Guokan Shang, Wensi Ding, Zekun Zhang, Antoine Tixier, Polykarpos Meladianos, Michalis Vazirgiannis, and Jean-Pierre Lorré. 2018 · 2018
Cited alongside, same era.
Abstractive summarization of reddit posts with multi-level memory networks
Byeongchang Kim, Hyunwoo Kim, and Gunhee Kim. 2019 · 2019
Cited alongside, same era.
Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 2019
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
Later among the works it cites.
Pegasus: Pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter Liu. 2020 · 2020
Later among the works it cites.
Extractive summarization as text matching
Ming Zhong, Pengfei Liu, Yiran Chen, Danqing Wang, Xipeng Qiu, and Xuanjing Huang. 2020 · 2020
Later among the works it cites.
Enhancing scientific papers summarization with citation graph
Chenxin An, Ming Zhong, Yiran Chen, Danqing Wang, Xipeng Qiu, and Xuanjing Huang. 2021 · 2021
Closest in time.
Contextualized rewriting for text summarization
Guangsheng Bao and Yue Zhang. 2021 · 2021
Closest in time.
Controllable generation from pre-trained language models via inverse prompting
Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, and Jie Tang. 2021 · 2021
Closest in time.