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Applying Transformer-based Text Summarization for Keyphrase Generation. (arXiv:2209.03791v2 [cs.CL] UPDATED)
Oct. 7, 2022, 1:17 a.m. | Anna Glazkova, Dmitry Morozov
cs.CL updates on arXiv.org arxiv.org
Keyphrases are crucial for searching and systematizing scholarly documents.
Most current methods for keyphrase extraction are aimed at the extraction of
the most significant words in the text. But in practice, the list of keyphrases
often includes words that do not appear in the text explicitly. In this case,
the list of keyphrases represents an abstractive summary of the source text. In
this paper, we experiment with popular transformer-based models for abstractive
text summarization using four benchmark datasets for keyphrase …
More from arxiv.org / cs.CL updates on arXiv.org
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