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We present Referee, a novel framework for sentence summarization that can be trained reference-free (i.e., requiring no gold summaries for supervision), while allowing direct control for compression ratio.
Language models are few-shot learners
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The information bottleneck method
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English gigaword
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Annotated gigaword
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Ramakanth Pasunuru, Han Guo, and Mohit Bansal. 2017 · 2017
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SEQˆ3: Differentiable sequence-to-sequence-to-sequence autoencoder for unsupervised abstractive sentence compression
Christos Baziotis, Ion Androutsopoulos, Ioannis Konstas, and Alexandros Potamianos. 2019 · 2019
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Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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BottleSum: Unsupervised and self-supervised sentence summarization using the information bottleneck principle
Peter West, Ari Holtzman, Jan Buys, and Yejin Choi. 2019 · 2019
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Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi. 2019 · 2019
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Discrete optimization for unsupervised sentence summarization with word-level extraction
Raphael Schumann, Lili Mou, Yao Lu, Olga Vechtomova, and Katja Markert. 2020 · 2020
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Bertscore: Evaluating text generation with bert
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Generating datasets with pretrained language models
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Efficient unsupervised sentence compression by fine-tuning transformers with reinforcement learning
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