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We study unsupervised multi-document summarization evaluation metrics, which require neither human-written reference summaries nor human annotations (e.g.
BERTScore: Evaluating Text Generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2019 · 1904
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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
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ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019 · 1909
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Better summarization evaluation with word embeddings for ROUGE
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Extractive summarization by maximizing semantic volume
Dani Yogatama, Fei Liu, and Noah A. Smith. 2015 · 1966
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Multi-document summarization by sentence extraction
Jade Goldstein, Vibhu Mittal, Jaime Carbonell, and Mark Kantrowitz. 2000 · 2000
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BLEU: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Lexrank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R. Radev. 2004 · 2004
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Evaluating content selection in summarization: The pyramid method
Ani Nenkova and Rebecca J. Passonneau. 2004 · 2004
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Clustering by passing messages between data points
Brendan J Frey and Delbert Dueck. 2007 · 2007
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The meteor metric for automatic evaluation of machine translation
Alon Lavie and Michael J. Denkowski. 2009 · 2009
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Framework of automatic text summarization using reinforcement learning
Seonggi Ryang and Takeshi Abekawa. 2012 · 2012
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Automatically assessing machine summary content without a gold standard
Annie Louis and Ani Nenkova. 2013 · 2013
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Fear the REAPER: A system for automatic multi-document summarization with reinforcement learning
Cody Rioux, Sadid A. Hasan, and Yllias Chali. 2014 · 2014
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From word embeddings to document distances
Matt J. Kusner, Yu Sun, Nicholas I. Kolkin, and Kilian Q. Weinberger. 2015 · 2015
Cited alongside, same era.
PEAK: pyramid evaluation via automated knowledge extraction
Qian Yang, Rebecca J. Passonneau, and Gerard de Melo. 2016 · 2016
Cited alongside, same era.
Learning to score system summaries for better content selection evaluation
Maxime Peyrard, Teresa Botschen, and Iryna Gurevych. 2017 · 2017
Cited alongside, same era.
Joint optimization of user-desired content in multi-document summaries by learning from user feedback
Estimating summary quality with pairwise preferences
Markus Zopf. 2018 · 2018
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Better rewards yield better summaries: Learning to summarise without references
Florian Böhm, Yang Gao, Christian M. Meyer, Ori Shapira, Ido Dagan, and Iryna Gurevych. 2019 · 2019
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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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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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A simple theoretical model of importance for summarization
Maxime Peyrard. 2019 · 2019
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Avinesh P.V.S and Christian M. Meyer. 2017 · 2017
Cited alongside, same era.
APRIL: interactively learning to summarise by combining active preference learning and reinforcement learning
Yang Gao, Christian M. Meyer, and Iryna Gurevych. 2018 · 2018
Cited alongside, same era.
Automatic pyramid evaluation exploiting EDU-based extractive reference summaries
Tsutomu Hirao, Hidetaka Kamigaito, and Masaaki Nagata. 2018 · 2018
Cited alongside, same era.
Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
Objective function learning to match human judgements for optimization-based summarization
Maxime Peyrard and Iryna Gurevych. 2018 · 2018
Cited alongside, same era.
A graph-theoretic summary evaluation for ROUGE
Elaheh ShafieiBavani, Mohammad Ebrahimi, Raymond Wong, and Fang Chen. 2018a · 2018
Cited alongside, same era.
Preference-based interactive multi-document summarisation
Yang Gao, Christian M. Meyer, and Iryna Gurevych. 2019a
Cited in the paper.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Answers unite! unsupervised metrics for reinforced summarization models
Thomas Scialom, Sylvain Lamprier, Benjamin Piwowarski, and Jacopo Staiano. 2019 · 2019
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Crowdsourcing lightweight pyramids for manual summary evaluation
Ori Shapira, David Gabay, Yang Gao, Hadar Ronen, Ramakanth Pasunuru, Mohit Bansal, Yael Amsterdamer, and Ido Dagan. 2019 · 2019
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The feasibility of embedding based automatic evaluation for single document summarization
Simeng Sun and Ani Nenkova. 2019 · 2019
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MoverScore: Text generation evaluating with contextualized embeddings and earth mover distance
Wei Zhao, Maxime Peyrard, Fei Liu, Yang Gao, Christian M. Meyer, and Steffen Eger. 2019 · 2019
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Sentence centrality revisited for unsupervised summarization
Hao Zheng and Mirella Lapata. 2019 · 2019
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