Automatic Summarization of Open-Domain Podcast Episodes

Roberta: A robustly optimized bert pretraining approach

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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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Exploring the limits of transfer learning with a unified text-to-text transformer

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Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019 · 1910

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Prophetnet: Predicting future n-gram for sequence-to-sequence pre-training

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Weizhen Qi, Yu Yan, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang, and Ming Zhou. 2020 · 2001

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From extractive to abstractive meeting summaries: Can it be done by sentence compression?

Fei Liu and Yang Liu. 2009 · 2009

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Unsupervised approaches for automatic keyword extraction using meeting transcripts

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Towards abstractive speech summarization: Exploring unsupervised and supervised approaches for spoken utterance compression

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Scoring sentence singletons and pairs for abstractive summarization

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TREC 2020 Podcasts Track Overview

Rosie Jones, Ben Carterette, Ann Clifton, Maria Eskevich, Gareth J. F. Jones, Jussi Karlgren, Aasish Pappu, Sravana Reddy, and Yongze Yu. 2020 · 2020

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How domain terminology affects meeting summarization performance

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A cascade approach to neural abstractive summarization with content selection and fusion

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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

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Controlling the amount of verbatim copying in abstractive summarization

Original

Kaiqiang Song, Bingqing Wang, Zhe Feng, Liu Ren, and Fei Liu. 2020 · 2020

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