吸引力的风格-内容二重性：通过解开缠绕学习撰写引人注目的标题
The Style-Content Duality of Attractiveness: Learning to Write Eye-Catching Headlines via Disentanglement
摘要：
醒目的标题是引发点击的第一个装置，在生产者和观众之间产生互惠效应。生产者可以获得更多的流量和利润，读者可以接触到优秀的文章。在生成有吸引力的标题时，重要的是不仅要捕捉有吸引力的内容，还要遵循引人注目的写作风格。在本文中，我们提出了一个基于解纠缠的吸引力标题生成器（DAHG），生成标题，捕捉有吸引力的内容，以下有吸引力的风格。具体而言，我们首先设计了一个解纠缠模块，将一个有吸引力的原型标题的风格和内容划分为潜在空间，并通过两个辅助约束来确保这两个空间确实是解纠缠的。然后，潜在内容信息用于进一步抛光文档表示并帮助捕获显著部分。最后，生成器以经过修饰的文档为输入，在吸引人的风格指导下生成标题。在公开的快宝数据集上的大量实验表明，DAHG达到了最先进的性能。人类评估还表明，DAHG触发的点击次数比现有模型多22%。
英文摘要：
Eye-catching headlines function as the first device to trigger more clicks, bringing reciprocal effect between producers and viewers. Producers can obtain more traffic and profits, and readers can have access to outstanding articles. When generating attractive headlines, it is important to not only capture the attractive content but also follow an eye-catching written style. In this paper, we propose a Disentanglement-based Attractive Headline Generator (DAHG) that generates headline which captures the attractive content following the attractive style. Concretely, we first devise a disentanglement module to divide the style and content of an attractive prototype headline into latent spaces, with two auxiliary constraints to ensure the two spaces are indeed disentangled. The latent content information is then used to further polish the document representation and help capture the salient part. Finally, the generator takes the polished document as input to generate headline under the guidance of the attractive style. Extensive experiments on the public Kuaibao dataset show that DAHG achieves state-of-the-art performance. Human evaluation also demonstrates that DAHG triggers 22% more clicks than existing models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
