Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization (2020.emnlp-main)
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| Challenge: | Existing studies on text summarization focus on single-speaker docs, scientific publications and encyclopedia articles. |
| Approach: | They propose a multi-view sequence-to-sequence model that extracts conversational structures from unstructured daily chats and incorporates different views to generate dialogue summaries. |
| Outcome: | The proposed model outperforms state-of-the-art models via automatic evaluation and human judgment on a large-scale dialogue summarization corpus. |
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