论文标题
图形元素的摘要
Summarization with Graphical Elements
论文作者
论文摘要
近年来，自动文本摘要已经取得了长足的进步。随着这一进展，问题出现了一个通常由自动摘要模型与用户需求保持一致的摘要类型。 Ter Hoeve等人（2020）对此问题负面回答。除其他外，他们建议专注于生成具有更多图形元素的摘要。这符合我们从心理语言学文献中了解人类如何处理文本的知识。从这两个角度开始，我们提出了一项新任务：用图形元素进行汇总，并验证这些摘要是否对大量的人有帮助。我们收集一个高质量的人类标记的数据集，以支持对任务的研究。我们提出了许多基线方法，这些方法表明该任务很有趣且具有挑战性。因此，通过这项工作，我们希望激发自动摘要社区中的一系列新研究。
Automatic text summarization has experienced substantial progress in recent years. With this progress, the question has arisen whether the types of summaries that are typically generated by automatic summarization models align with users' needs. Ter Hoeve et al (2020) answer this question negatively. Amongst others, they recommend focusing on generating summaries with more graphical elements. This is in line with what we know from the psycholinguistics literature about how humans process text. Motivated from these two angles, we propose a new task: summarization with graphical elements, and we verify that these summaries are helpful for a critical mass of people. We collect a high quality human labeled dataset to support research into the task. We present a number of baseline methods that show that the task is interesting and challenging. Hence, with this work we hope to inspire a new line of research within the automatic summarization community.
