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Distant Supervision for Extractive Question Summarization
Questions are often lengthy and difficult to understand because they tend to contain peripheral information. Previous work relies on costly human-annotated data or question-title pairs. In this work, we propose a distant supervision framework that can train a question summarizer without annotation c...
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| Vydáno v: | Advances in Information Retrieval |
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| Hlavní autoři: | , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2020
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7148018/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-45442-5_23 |
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