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Simple Unsupervised Summarization by Contextual Matching

2019-07-31ACL 2019Code Available0· sign in to hype

Jiawei Zhou, Alexander M. Rush

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Abstract

We propose an unsupervised method for sentence summarization using only language modeling. The approach employs two language models, one that is generic (i.e. pretrained), and the other that is specific to the target domain. We show that by using a product-of-experts criteria these are enough for maintaining continuous contextual matching while maintaining output fluency. Experiments on both abstractive and extractive sentence summarization data sets show promising results of our method without being exposed to any paired data.

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Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
GigaWordContextual MatchROUGE-126.48Unverified

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