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Automatic summary assessment is useful for both machine-generated and human-produced summaries.
On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
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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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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
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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
Rada Mihalcea and Paul Tarau. 2004 · 2004
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End-to-end semantics-based summary quality assessment for single-document summarization
Forrest Sheng Bao, Hebi Li, Ge Luo, Cen Chen, Yinfei Yang, Youbiao He, and Minghui Qiu. 2020 · 2005
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Overview of the tac 2008 update summarization task
Hoa Trang Dang and Karolina Owczarzak. 2008 · 2008
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Overview of the tac 2009 summarization track
Hoa Trang Dang and Karolina Owczarzak. 2009 · 2009
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Automatic summarization of open-domain podcast episodes
Kaiqiang Song, Chen Li, Xiaoyang Wang, Dong Yu, and Fei Liu. 2020 · 2011
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CUED_speech at TREC 2020 Podcast Summarisation Track
Potsawee Manakul and Mark Gales. 2020 · 2012
Earlier work this paper cites.
Leveraging linguistic structure for open domain information extraction
Gabor Angeli, Melvin Jose Johnson Premkumar, and Christopher D. Manning. 2015 · 2015
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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A two-phase approach for abstractive podcast summarization
Chujie Zheng, Kunpeng Zhang, Harry Jiannan Wang, and Ling Fan. 2020 · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
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NewsQA: A machine comprehension dataset
Adam Trischler, Tong Wang, Xingdi Yuan, Justin Harris, Alessandro Sordoni, Philip Bachman, and Kaheer Suleman. 2017 · 2017
Cited alongside, same era.
Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 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.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 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
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Glasgow Representation and Information Learning Lab (GRILL) at TREC 2020 Podcasts Track
Paul Owoicho and Jeff Dalton. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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COMET: A neural framework for MT evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020 · 2020
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BLEURT: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
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Ben Goodrich, Vinay Rao, Peter J. Liu, and Mohammad Saleh. 2019 · 2019
Cited alongside, same era.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
Automatic learner summary assessment for reading comprehension
Menglin Xia, Ekaterina Kochmar, and Ted Briscoe. 2019 · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Re-evaluating evaluation in text summarization
Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, Pengfei Liu, and Graham Neubig. 2020 · 2020
Cited alongside, same era.
100,000 podcasts: A spoken English document corpus
Ann Clifton, Sravana Reddy, Yongze Yu, Aasish Pappu, Rezvaneh Rezapour, Hamed Bonab, Maria Eskevich, Gareth Jones, Jussi Karlgren, Ben Carterette, and Rosie Jones. 2020 · 2020
Cited alongside, same era.
FEQA: A question answering evaluation framework for faithfulness assessment in abstractive summarization
Esin Durmus, He He, and Mona Diab. 2020 · 2020
Cited alongside, same era.
Asking and answering questions to evaluate the factual consistency of summaries
Alex Wang, Kyunghyun Cho, and Mike Lewis. 2020 · 2020
Later among the works it cites.
Unsupervised reference-free summary quality evaluation via contrastive learning
Hanlu Wu, Tengfei Ma, Lingfei Wu, Tariro Manyumwa, and Shouling Ji. 2020 · 2020
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Pegasus: Pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter Liu. 2020 · 2020
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Bertscore: Evaluating text generation with bert
Tianyi Zhang*, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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Towards question-answering as an automatic metric for evaluating the content quality of a summary
Daniel Deutsch, Tania Bedrax-Weiss, and Dan Roth. 2021 · 2021
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Summeval: Re-evaluating summarization evaluation
Alexander R Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021 · 2021
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Long-span summarization via local attention and content selection
Potsawee Manakul and Mark Gales. 2021 · 2021
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QuestEval: Summarization asks for fact-based evaluation
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano, Alex Wang, and Patrick Gallinari. 2021 · 2021
Later among the works it cites.
Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
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Ffci: A framework for interpretable automatic evaluation of summarization
Fajri Koto, Timothy Baldwin, and Jey Han Lau. 2022 · 2022
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