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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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Bibliografiske detaljer
Udgivet i:Advances in Information Retrieval
Main Authors: Ishigaki, Tatsuya, Machida, Kazuya, Kobayashi, Hayato, Takamura, Hiroya, Okumura, Manabu
Format: Artigo
Sprog:Inglês
Udgivet: 2020
Fag:
Online adgang: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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