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Dialogue summarization aims to condense the lengthy dialogue into a concise summary, and has recently achieved significant progress.
On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
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Binary codes capable of correcting deletions, insertions, and reversals
Vladimir I. Levenshtein. 1965 · 1965
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Measuring nominal scale agreement among many raters
J.L. Fleiss et al. 1971 · 1971
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Errors of omission in translation
Graham Russell. 1999 · 1999
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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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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Summarizing email threads
Owen Rambow, Lokesh Shrestha, John Chen, and Chirsty Lauridsen. 2004 · 2004
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Summarizing spoken and written conversations
Gabriel Murray and Giuseppe Carenini. 2008 · 2008
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The relevance of addition, omission and deletion (aod) in translation
Vipin Sharma. 2015 · 2015
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Order matters: Sequence to sequence for sets
Oriol Vinyals, Samy Bengio, and Manjunath Kudlur. 2015 · 2015
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Modeling coverage for neural machine translation
Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, and Hang Li. 2016 · 2016
Earlier work this paper cites.
Summarunner: A recurrent neural network based sequence model for extractive summarization of documents
Ramesh Nallapati, Feifei Zhai, and Bowen Zhou. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz 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
Cited alongside, same era.
Samsum corpus: A human-annotated dialogue dataset for abstractive summarization
Bogdan Gliwa, Iwona Mochol, Maciej Biesek, and Aleksander Wawer. 2019 · 2019
Cited alongside, same era.
Neural text summarization: A critical evaluation
Wojciech Kryściński, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
Cited alongside, same era.
Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 2019
Cited alongside, same era.
Reducing word omission errors in neural machine translation: A contrastive learning approach
Zonghan Yang, Yong Cheng, Yang Liu, and Maosong Sun. 2019 · 2019
Cited alongside, same era.
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 2019
Summarizing medical conversations via identifying important utterances
Yan Song, Yuanhe Tian, Nan Wang, and Fei Xia. 2020 · 2020
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Joint contextual modeling for ASR correction and language understanding
Yue Weng, Sai Sumanth Miryala, Chandra Khatri, Runze Wang, Huaixiu Zheng, Piero Molino, Mahdi Namazifar, Alexandros Papangelis, Hugh Williams, Franziska Bell, and Gökhan Tür. 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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Dialogsum: A real-life scenario dialogue summarization dataset
Yulong Chen, Yang Liu, Liang Chen, and Yue Zhang. 2021 · 2021
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Tweetsumm-a dialog summarization dataset for customer service
Guy Feigenblat, Chulaka Gunasekara, Benjamin Sznajder, Sachindra Joshi, David Konopnicki, and Ranit Aharonov. 2021 · 2021
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Cited alongside, same era.
Searching for effective neural extractive summarization: What works and what’s next
Ming Zhong, Pengfei Liu, Danqing Wang, Xipeng Qiu, and Xuan-Jing Huang. 2019 · 2019
Cited alongside, same era.
Multi-view sequence-to-sequence models with conversational structure for abstractive dialogue summarization
Jiaao Chen and Diyi Yang. 2020 · 2020
Cited alongside, same era.
Dr. summarize: Global summarization of medical dialogue by exploiting local structures
Anirudh Joshi, Namit Katariya, Xavier Amatriain, and Anitha Kannan. 2020 · 2020
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
Cited alongside, same era.
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, Peter J Liu, et al. 2020 · 2020
Cited alongside, same era.
Bleurt: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
Cited alongside, same era.
Controllable neural dialogue summarization with personal named entity planning
Zhengyuan Liu and Nancy Chen. 2021 · 2021
Later among the works it cites.
Coreference-aware dialogue summarization
Zhengyuan Liu, Ke Shi, and Nancy Chen. 2021 · 2021
Later among the works it cites.
Emailsum: Abstractive email thread summarization
Shiyue Zhang, Asli Celikyilmaz, Jianfeng Gao, and Mohit Bansal. 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 Hassan, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, et al. 2021 · 2021
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Low-resource dialogue summarization with domain-agnostic multi-source pretraining
Yicheng Zou, Bolin Zhu, Xingwu Hu, Tao Gui, and Qi Zhang. 2021c · 2021
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A survey on dialogue summarization: Recent advances and new frontiers
Xiachong Feng, Xiaocheng Feng, and Bing Qin. 2022 · 2022
Closest in time.
CONFIT: Toward faithful dialogue summarization with linguistically-informed contrastive fine-tuning
Xiangru Tang, Arjun Nair, Borui Wang, Bingyao Wang, Jai Desai, Aaron Wade, Haoran Li, Asli Celikyilmaz, Yashar Mehdad, and Dragomir Radev. 2022 · 2022
Closest in time.