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PPSGen: Learning-Based Presentation Slides Generation for Academic Papers

机译:PPSGen:学术论文的基于学习的演示幻灯片生成

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In this paper, we investigate a very challenging task of automatically generating presentation slides for academic papers. The generated presentation slides can be used as drafts to help the presenters prepare their formal slides in a quicker way. A novel system called PPSGen is proposed to address this task. It first employs the regression method to learn the importance scores of the sentences in an academic paper, and then exploits the integer linear programming (ILP) method to generate well-structured slides by selecting and aligning key phrases and sentences. Evaluation results on a test set of 200 pairs of papers and slides collected on the web demonstrate that our proposed PPSGen system can generate slides with better quality. A user study is also illustrated to show that PPSGen has a few evident advantages over baseline methods.
机译:在本文中,我们调查了自动生成学术论文演示幻灯片的一项非常艰巨的任务。生成的演示幻灯片可以用作草稿,以帮助演示者更快地准备其正式幻灯片。提出了一种称为PPSGen的新颖系统来解决此任务。它首先采用回归方法来学习学术论文中句子的重要性分数,然后利用整数线性规划(ILP)方法通过选择和对齐关键短语和句子来生成结构合理的幻灯片。在Web上收集的200对论文和幻灯片的测试集上的评估结果表明,我们提出的PPSGen系统可以生成质量更高的幻灯片。还显示了一项用户研究,以表明PPSGen与基线方法相比具有一些明显的优势。

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