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Dialogue summarization aims to condense the original dialogue into a shorter version covering salient information, which is a crucial way to reduce dialogue data overload.
Constructing literature abstracts by computer: techniques and prospects
Chris D Paice · 1990
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The icsi meeting corpus
Adam Janin, Don Baron, Jane Edwards, Dan Ellis, David Gelbart, Nelson Morgan, Barbara Peskin, Thilo Pfau, Elizabeth Shriberg, Andreas Stolcke, et al · 2003
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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The ami meeting corpus: A pre-announcement
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A publicly available annotated corpus for supervised email summarization
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Summarunner: A recurrent neural network based sequence model for extractive summarization of documents
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Attention is all you need
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Unsupervised abstractive meeting summarization with multi-sentence compression and budgeted submodular maximization
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SAMSum corpus: A human-annotated dialogue dataset for abstractive summarization
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Automatically generating psychiatric case notes from digital transcripts of doctor-patient conversations
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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
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Automatic dialogue summary generation for customer service
Chunyi Liu, Peng Wang, Jiang Xu, Zang Li, and Jieping Ye · 2019
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Topic-aware pointer-generator networks for summarizing spoken conversations
Zhengyuan Liu, A. Ng, Sheldon Lee Shao Guang, AiTi Aw, and Nancy F. Chen · 2019
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Multi-view sequence-to-sequence models with conversational structure for abstractive dialogue summarization
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Seppo Enarvi, Marilisa Amoia, Miguel Del-Agua Teba, Brian Delaney, Frank Diehl, Stefan Hahn, Kristina Harris, Liam McGrath, Yue Pan, Joel Pinto, Luca Rubini, Miguel Ruiz, Gagandeep Singh, Fabian Stemmer, Weiyi Sun, Paul Vozila, Thomas Lin, and Ranjani Ramamurthy · 2020
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Generating SOAP notes from doctor-patient conversations using modular summarization techniques
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CSDS: A fine-grained Chinese dataset for customer service dialogue summarization
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GupShup: Summarizing open-domain code-switched conversations
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DIALOGPT : Large-scale generative pre-training for conversational response generation
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A hierarchical network for abstractive meeting summarization with cross-domain pretraining
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Simple conversational data augmentation for semi-supervised abstractive dialogue summarization
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Laiba Mehnaz, Debanjan Mahata, Rakesh Gosangi, Uma Sushmitha Gunturi, Riya Jain, Gauri Gupta, Amardeep Kumar, Isabelle G. Lee, Anish Acharya, and Rajiv Ratn Shah · 2021
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Investigating crowdsourcing protocols for evaluating the factual consistency of summaries
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QMSum: A new benchmark for query-based multi-domain meeting summarization
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Unsupervised summarization for chat logs with topic-oriented ranking and context-aware auto-encoders
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A survey on cross-lingual summarization
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Dialoglm: Pre-trained model for long dialogue understanding and summarization
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