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arXiv · 1909.11974

Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation

Ze Yang·Can Xu·Wei Wu·Zhoujun Li
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Abstract

Automatic news comment generation is a new testbed for techniques of natural language generation. In this paper, we propose a "read-attend-comment" procedure for news comment generation and formalize the procedure with a reading network and a generation network. The reading network comprehends a news article and distills some important points from it, then the generation network creates a comment by attending to the extracted discrete points and the news title. We optimize the model in an end-to-end manner by maximizing a variational lower bound of the true objective using the back-propagation algorithm. Experimental results on two datasets indicate that our model can significantly outperform existing methods in terms of both automatic evaluation and human judgment.

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Ze Yang, Can Xu, Wei Wu, Zhoujun Li. 2019-09-26. Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation. https://arxiv.org/abs/1909.11974

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