Papers with ICSI
Improving Abstractive Dialogue Summarization with Hierarchical Pretraining and Topic Segment (2021.findings-emnlp)
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| Challenge: | Existing methods for meeting summary have limited the ability to deal with long-term dependency. |
| Approach: | They propose a hierarchical transformer encoder-decoder network with multi-task pre-training to capture key sentences at word level and generate them at word-level. |
| Outcome: | The proposed model is superior to the previous methods in meeting summary datasets AMI and ICSI. |
SummN: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents (2022.acl-long)
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Yusen Zhang, Ansong Ni, Ziming Mao, Chen Henry Wu, Chenguang Zhu, Budhaditya Deb, Ahmed Awadallah, Dragomir Radev, Rui Zhang
| Challenge: | Existing methods to handle long text are limited due to time and memory complexity and limited input lengths. |
| Approach: | They propose a multi-stage split-then-summarize framework for long input summarization . their framework can process input text of arbitrary length by adjusting the number of stages . |
| Outcome: | The proposed framework outperforms existing methods on three long meeting summarization datasets and on a long document summarizing dataset. |
Reconstruct Before Summarize: An Efficient Two-Step Framework for Condensing and Summarizing Meeting Transcripts (2023.emnlp-main)
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| Challenge: | Existing approaches to meeting summarization are limited due to noise, lengthy transcripts, and scattered salient information. |
| Approach: | They propose a two-step framework for meeting summarization that leverages a self-supervised paradigm to reconstruct transcripts and a relative positional bucketing algorithm to equip models to generate the summary. |
| Outcome: | The proposed method significantly reduces memory consumption and processing time on two meeting summarization datasets. |