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Models pretrained with self-supervised objectives on large text corpora achieve state-of-the-art performance on English text summarization tasks.
Unsupervised data augmentation for consistency training
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Lexrank: Graph-based lexical centrality as salience in text summarization
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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TextRank: Bringing order into text
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Summeval: Re-evaluating summarization evaluation
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The new york times annotated corpus
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Gsum: A general framework for guided neural abstractive summarization
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Logan Lebanoff, Kaiqiang Song, and Fei Liu. 2018 · 2018
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Neural text summarization: A critical evaluation
Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
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Facebook FAIR’s WMT19 news translation task submission
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fairseq: A fast, extensible toolkit for sequence modeling
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BIGPATENT: A large-scale dataset for abstractive and coherent summarization
Eva Sharma, Chen Li, and Lu Wang. 2019 · 2019
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Exploring domain shift in extractive text summarization
Danqing Wang, Pengfei Liu, Ming Zhong, Jie Fu, Xipeng Qiu, and Xuanjing Huang. 2019 · 2019
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Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Eric Chu and Peter J. Liu. 2019 · 2019
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Earlier isn’t always better: Sub-aspect analysis on corpus and system biases in summarization
Taehee Jung, Dongyeop Kang, Lucas Mentch, and Eduard Hovy. 2019 · 2019
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Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter J. Liu. 2019 · 2019
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Sentence centrality revisited for unsupervised summarization
Hao Zheng and Mirella Lapata. 2019 · 2019
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Simple unsupervised summarization by contextual matching
Jiawei Zhou and Alexander Rush. 2019 · 2019
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Compressive summarization with plausibility and salience modeling
Shrey Desai, Jiacheng Xu, and Greg Durrett. 2020 · 2020
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Evaluating the factual consistency of abstractive text summarization
Wojciech Kryscinski, Bryan McCann, Caiming Xiong, and Richard Socher. 2020 · 2020
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The summary loop: Learning to write abstractive summaries without examples
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TED: A pretrained unsupervised summarization model with theme modeling and denoising
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