An Exploratory Study on Long Dialogue Summarization: What Works and What’s Next-Reference-Cited by-同舟云学术

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An Exploratory Study on Long Dialogue Summarization: What Works and What’s Next

Published:2021 Issue: Volume: Page:
ISSN:
Container-title:Findings of the Association for Computational Linguistics: EMNLP 2021
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Author:

Zhang Yusen,Ni Ansong,Yu Tao,Zhang Rui,Zhu Chenguang,Deb Budhaditya,Celikyilmaz Asli,Awadallah Ahmed Hassan,Radev Dragomir

Publisher

Association for Computational Linguistics

Cited by 14 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. A Novel Topic Segmentation Approach for Enhanced Dialogue Summarization;World Journal of Innovation and Modern Technology;2024-08-20

2. Multistage Mixed-Attention Unsupervised Keyword Extraction for Summary Generation;Applied Sciences;2024-03-13

3. Adapter-Based Selective Knowledge Distillation for Federated Multi-Domain Meeting Summarization;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

4. A Comprehensive Evaluation of Large Language Models for Turkish Abstractive Dialogue Summarization;IEEE Access;2024

5. Aspect-based Meeting Transcript Summarization: A Two-Stage Approach with Weak Supervision on Sentence Classification;2023 IEEE International Conference on Big Data (BigData);2023-12-15

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