A Reinforced Topic-Aware Convolutional Sequence-to-Sequence Model for Abstractive Text Summarization

9 May 2018Li WangJunlin YaoYunzhe TaoLi ZhongWei LiuQiang Du

In this paper, we propose a deep learning approach to tackle the automatic summarization tasks by incorporating topic information into the convolutional sequence-to-sequence (ConvS2S) model and using self-critical sequence training (SCST) for optimization. Through jointly attending to topics and word-level alignment, our approach can improve coherence, diversity, and informativeness of generated summaries via a biased probability generation mechanism... (read more)

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