论文标题
索赔：比较和对比有关有争议的问题的主张
ClaimDiff: Comparing and Contrasting Claims on Contentious Issues
论文作者
论文摘要
随着检测错误信息的越来越重要，许多研究集中在通过检索证据来验证事实主张。但是，规范的事实验证任务不适用于在事实一致的主张上捕捉细微的差异，这可能仍然是偏见读者的，尤其是在有争议的政治或经济问题上。我们的基本假设是，在受信任的来源中，一个人的论点不一定比另一个更为真实，需要比较而不是验证。在这项研究中，我们提出了索赔式，这是一个新型数据集，主要侧重于比较索赔对之间的细微差别。在索赔迪夫中，我们提供了268篇新闻文章的2,941个注释的索赔对。我们观察到，尽管人类能够检测到主张之间的细微差别，但强大的基本线很难检测到它们，表现出与人类绝对差距的19％。我们希望这项最初的研究能够通过机械辅助比较来帮助读者对有争议的问题无公正。
With the growing importance of detecting misinformation, many studies have focused on verifying factual claims by retrieving evidence. However, canonical fact verification tasks do not apply to catching subtle differences in factually consistent claims, which might still bias the readers, especially on contentious political or economic issues. Our underlying assumption is that among the trusted sources, one's argument is not necessarily more true than the other, requiring comparison rather than verification. In this study, we propose ClaimDiff, a novel dataset that primarily focuses on comparing the nuance between claim pairs. In ClaimDiff, we provide 2,941 annotated claim pairs from 268 news articles. We observe that while humans are capable of detecting the nuances between claims, strong baselines struggle to detect them, showing over a 19% absolute gap with the humans. We hope this initial study could help readers to gain an unbiased grasp of contentious issues through machine-aided comparison.
