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Meeting minutes record any subject matters discussed, decisions reached and actions taken at meetings.
On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
Earlier work this paper cites.
Prediction and entropy of printed english
C. E. Shannon. 1951 · 1951
Earlier work this paper cites.
Collection of spontaneous speech for the ATIS domain and comparative analyses of data collected at MIT and TI
Joseph Polifroni, Stephanie Seneff, and Victor W. Zue. 1991 · 1991
Earlier work this paper cites.
The icsi meeting corpus
A. Janin, D. Baron, J. Edwards, D. Ellis, D. Gelbart, N. Morgan, B. Peskin, T. Pfau, E. Shriberg, A. Stolcke, and C. Wooters. 2003 · 2003
Earlier work this paper cites.
LexRank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R. Radev. 2004 · 2004
Earlier work this paper cites.
ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
TextRank: Bringing order into text
Rada Mihalcea and Paul Tarau. 2004 · 2004
Earlier work this paper cites.
The 2005 ami system for the transcription of speech in meetings
Thomas Hain, Lukas Burget, John Dines, Giulia Garau, Martin Karafiat, Mike Lincoln, Iain McCowan, Darren Moore, Vincent Wan, Roeland Ordelman, and Steve Renals. 2006 · 2005
Earlier work this paper cites.
Comparing lexical, acoustic/prosodic, structural and discourse features for speech summarization
Sameer Maskey and Julia Hirschberg. 2005 · 2005
Earlier work this paper cites.
A skip-chain conditional random field for ranking meeting utterances by importance
Michel Galley. 2006 · 2006
Earlier work this paper cites.
Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
Lucy Vanderwende, Hisami Suzuki, Chris Brockett, and Ani Nenkova. 2007 · 2007
Earlier work this paper cites.
Automatic decision detection in meeting speech
Pei-Yun Hsueh and Johanna D. Moore. 2008 · 2008
Earlier work this paper cites.
Summarizing spoken and written conversations
Gabriel Murray and Giuseppe Carenini. 2008 · 2008
Earlier work this paper cites.
A global optimization framework for meeting summarization
Daniel Gillick, Korbinian Riedhammer, Benoît Favre, and Dilek Hakkani-Tur. 2009 · 2009
Earlier work this paper cites.
Exploring content models for multi-document summarization
Aria Haghighi and Lucy Vanderwende. 2009 · 2009
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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
Feifan Liu, Deana Pennell, Fei Liu, and Yang Liu. 2009 · 2009
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Summarizing multiple spoken documents: finding evidence from untranscribed audio
Xiaodan Zhu, Gerald Penn, and Frank Rudzicz. 2009 · 2009
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Two-layer mutually reinforced random walk for improved multi-party meeting summarization
Yun-Nung Chen and Florian Metze. 2012 · 2012
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Neural text summarization: A critical evaluation
Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
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Analyzing sentence fusion in abstractive summarization
Logan Lebanoff, John Muchovej, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, and Fei Liu. 2019 · 2019
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Keep meeting summaries on topic: Abstractive multi-modal meeting summarization
Manling Li, Lingyu Zhang, Heng Ji, and Richard J. Radke. 2019 · 2019
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Generating summaries with topic templates and structured convolutional decoders
Laura Perez-Beltrachini, Yang Liu, and Mirella Lapata. 2019 · 2019
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Longformer: The long-document transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020 · 2020
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Yashar Mehdad, Giuseppe Carenini, Frank Tompa, and Raymond T. Ng. 2013 · 2013
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Domain-independent abstract generation for focused meeting summarization
Lu Wang and Claire Cardie. 2013 · 2013
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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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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Fast abstractive summarization with reinforce-selected sentence rewriting
Yen-Chun Chen and Mohit Bansal. 2018 · 2018
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Bottom-up abstractive summarization
Sebastian Gehrmann, Yuntian Deng, and Alexander Rush. 2018 · 2018
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Content selection in deep learning models of summarization
Chris Kedzie, Kathleen McKeown, and Hal Daumé III. 2018 · 2018
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Reformer: The efficient transformer
Nikita Kitaev, Lukasz Kaiser, and Anselm Levskaya. 2020 · 2020
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How domain terminology affects meeting summarization performance
Jia Jin Koay, Alexander Roustai, Xiaojin Dai, Dillon Burns, Alec Kerrigan, and Fei Liu. 2020 · 2020
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The summary loop: Learning to write abstractive summaries without examples
Philippe Laban, Andrew Hsi, John Canny, and Marti A. Hearst. 2020 · 2020
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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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Summarizing medical conversations via identifying important utterances
Yan Song, Yuanhe Tian, Nan Wang, and Fei Xia. 2020 · 2020
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A hierarchical network for abstractive meeting summarization with cross-domain pretraining
Chenguang Zhu, Ruochen Xu, Michael Zeng, and Xuedong Huang. 2020 · 2020
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Google meet tips and tricks
Jon Martindale. 2021 · 2021
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QMSum: A new benchmark for query-based multi-domain meeting summarization
Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed H. Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, and Dragomir Radev. 2021 · 2021
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