Compressive Summarization with Plausibility and Salience Modeling

empirical methods in natural language processing, pp. 6259-6274, 2020.

Other Links: arxiv.org|academic.microsoft.com

Abstract:

Compressive summarization systems typically rely on a seed set of syntactic rules to determine under what circumstances deleting a span is permissible, then learn which compressions to actually apply by optimizing for ROUGE. In this work, we propose to relax these explicit syntactic constraints on candidate spans, and instead leave the de...More

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