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Extractive Summarizer for Scholarly Articles

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arxiv 2008.11290 v1 pith:GHGGXERM submitted 2020-08-25 cs.CL cs.IRcs.LG

classification cs.CLcs.IRcs.LG
keywords extractivesentencesarticlesauthorsdeepestimatedgoldimportance
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We introduce an extractive method that will summarize long scientific papers. Our model uses presentation slides provided by the authors of the papers as the gold summary standard to label the sentences. The sentences are ranked based on their novelty and their importance as estimated by deep neural networks. Our window-based extractive labeling of sentences results in the improvement of at least 4 ROUGE1-Recall points.

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