资源分类
》 资源 》论文》Simple Unsupervised Summarization by Contextual Matching

Simple Unsupervised Summarization by Contextual Matching

2019-09-23 | |  114 |   57 |   0 0 0
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 productof-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

上一篇：Sentence Centrality Revisited for Unsupervised Summarization

下一篇：Studying Summarization Evaluation Metrics in the Appropriate Scoring

用户评价
全部评价

热门资源

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...