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Most studies on abstractive summarization report ROUGE scores between system and reference summaries.
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.
Evaluating the factual consistency of abstractive text summarization
Wojciech Kryscinski, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 1910
Earlier work this paper cites.
Multi-document summarization by sentence extraction
Jade Goldstein, Vibhu Mittal, Jaime Carbonell, and Mark Kantrowitz. 2000 · 2000
Earlier work this paper cites.
Statistics-based summarization - step one: Sentence compression
Kevin Knight and Daniel Marcu. 2000 · 2000
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Automatic Summarization
Inderjeet Mani. 2001 · 2001
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English Gigaword (LDC2003T05)
David Graff and Christopher Cieri. 2003 · 2003
Earlier work this paper cites.
Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard Hovy. 2003 · 2003
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LexRank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R. Radev. 2004 · 2004
Earlier work this paper cites.
Applying conditional random fields to Japanese morphological analysis
Taku Kudo, Kaoru Yamamoto, and Yuji Matsumoto. 2004 · 2004
Earlier work this paper cites.
Graph-based ranking algorithms for sentence extraction, applied to text summarization
Rada Mihalcea. 2004 · 2004
Earlier work this paper cites.
Global inference for sentence compression an integer linear programming approach
James Clarke and Mirella Lapata. 2008 · 2008
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A class of submodular functions for document summarization
Hui Lin and Jeff Bilmes. 2011 · 2011
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Annotated Gigaword
Courtney Napoles, Matthew Gormley, and Benjamin Van Durme. 2012 · 2012
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
A neural attention model for abstractive sentence summarization
Alexander M. Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
Cited alongside, same era.
Neural headline generation on abstract meaning representation
Sho Takase, Jun Suzuki, Naoaki Okazaki, Tsutomu Hirao, and Masaaki Nagata. 2016 · 2016
Cited alongside, same era.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Lukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2016 · 2016
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Later among the works it cites.
On the abstractiveness of neural document summarization
Fangfang Zhang, Jin-ge Yao, and Rui Yan. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019 · 2019
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Ranking generated summaries by correctness: An interesting but challenging application for natural language inference
Tobias Falke, Leonardo F. R. Ribeiro, Prasetya Ajie Utama, Ido Dagan, and Iryna Gurevych. 2019 · 2019
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Cited alongside, same era.
From neural sentence summarization to headline generation: A coarse-to-fine approach
Jiwei Tan, Xiaojun Wan, and Jianguo Xiao. 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.
Selective encoding for abstractive sentence summarization
Qingyu Zhou, Nan Yang, Furu Wei, and Ming Zhou. 2017 · 2017
Cited alongside, same era.
Soft layer-specific multi-task summarization with entailment and question generation
Han Guo, Ramakanth Pasunuru, and Mohit Bansal. 2018 · 2018
Cited alongside, same era.
Reducing odd generation from neural headline generation
Shun Kiyono, Sho Takase, Jun Suzuki, Naoaki Okazaki, Kentaro Inui, and Masaaki Nagata. 2018 · 2018
Cited alongside, same era.
SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
Cited alongside, same era.
Ensure the correctness of the summary: Incorporate entailment knowledge into abstractive sentence summarization
Haoran Li, Junnan Zhu, Jiajun Zhang, and Chengqing Zong. 2018 · 2018
Cited alongside, same era.
A large-scale multi-length headline corpus for improving length-constrained headline generation model evaluation
Yuta Hitomi, Yuya Taguchi, Hideaki Tamori, Ko Kikuta, Jiro Nishitoba, Naoaki Okazaki, Kentaro Inui, and Manabu Okumura. 2019 · 2019
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BERT pretrained model trained on Japanese Wikipedia articles
Yohei Kikuta. 2019 · 2019
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Neural text summarization: A critical evaluation
Wojciech Kryściński, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
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Neural headline generation with self-training
Kazuma Murao, Shintaro Takemae, Hayato Kobayashi, Taichi Yatsuka, Masaki Noguchi, Hitoshi Nishikawa, and Takenobu Tokunaga. 2019 · 2019
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fairseq: A fast, extensible toolkit for sequence modeling
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli. 2019 · 2019
Later among the works it cites.
Mass: Masked sequence to sequence pre-training for language generation
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu. 2019 · 2019
Later among the works it cites.
BiSET: Bi-directional selective encoding with template for abstractive summarization
Kai Wang, Xiaojun Quan, and Rui Wang. 2019 · 2019
Later among the works it cites.