Simple Unsupervised Summarization by Contextual Matching

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Authors Alexander M. Rush, Jiawei Zhou
Journal/Conference Name ACL 2019 7
Paper Category
Paper 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.
Date of publication 2019
Code Programming Language Python
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