Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization-Reference-Cited by-同舟云学术

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Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization

Published:2020 Issue: Volume: Page:
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Container-title:Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
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Author:

Chen Jiaao,Yang Diyi

Publisher

Association for Computational Linguistics

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Extractive Conversation Summarization Driven by Textual Entailment Prediction;2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT);2023-10-18

2. Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches, and Future Directions;ACM Computing Surveys;2023-10-05

3. DiscSumm: A Discourse Based Saliency Model to Generate Abstract Summaries for Conversation;2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2023-10-01

4. Unsupervised Dialogue Topic Segmentation with Topic-aware Contrastive Learning;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

5. WHORU: Improving Abstractive Dialogue Summarization with Personal Pronoun Resolution;Electronics;2023-07-16

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