TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Extractive Text Summarization	CNN / Daily Mail	REFRESH	ROUGE-2	18.2	# 12
Extractive Text Summarization	CNN / Daily Mail	REFRESH	ROUGE-1	40.0	# 13
Extractive Text Summarization	CNN / Daily Mail	REFRESH	ROUGE-L	36.6	# 11

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Ranking Sentences for Extractive Summarization with Reinforcement Learning

NAACL 2018 · Shashi Narayan, Shay B. Cohen, Mirella Lapata ·

Single document summarization is the task of producing a shorter version of a document while preserving its principal information content. In this paper we conceptualize extractive summarization as a sentence ranking task and propose a novel training algorithm which globally optimizes the ROUGE evaluation metric through a reinforcement learning objective. We use our algorithm to train a neural summarization model on the CNN and DailyMail datasets and demonstrate experimentally that it outperforms state-of-the-art extractive and abstractive systems when evaluated automatically and by humans.