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Summarization
5 papers
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@@ -216,7 +216,7 @@ used as source texts documents achieved from existing datasets. The chosen datas
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  datasets with short texts (with an average of 600 words) or datasets with longer texts with
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  extractive human summaries. In order to fill the gap and provide a dataset with long text
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  documents for abstractive summarization, the authors compiled two new datasets with scientific
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- papers from arXiv and PubMed databases. Scientific papers are especially convenient given the
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  desired kind of ATS the authors mean to achieve, and that is due to their large length and
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  the fact that each one contains an abstractive summary made by its author – i.e., the paper’s
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  abstract.
 
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  datasets with short texts (with an average of 600 words) or datasets with longer texts with
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  extractive human summaries. In order to fill the gap and provide a dataset with long text
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  documents for abstractive summarization, the authors compiled two new datasets with scientific
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+ papers from arXiv and PubMed databases. Scientific papers are specially convenient given the
220
  desired kind of ATS the authors mean to achieve, and that is due to their large length and
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  the fact that each one contains an abstractive summary made by its author – i.e., the paper’s
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  abstract.