BottleSum: Unsupervised and Self-supervised Sentence Summarization using the Information Bottleneck Principle

IJCNLP 2019 Peter WestAri HoltzmanJan BuysYejin Choi

The principle of the Information Bottleneck (Tishby et al. 1999) is to produce a summary of information X optimized to predict some other relevant information Y. In this paper, we propose a novel approach to unsupervised sentence summarization by mapping the Information Bottleneck principle to a conditional language modelling objective: given a sentence, our approach seeks a compressed sentence that can best predict the next sentence... (read more)

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