The World Wide Web and social media platforms have become popular sources for news and information. Typically, multimodal information, e.g., image and text is used to convey information more effectively and to attract attention. While in most cases image content is decorative or depicts additional information, it has also been leveraged to spread misinformation and rumors in recent years. In this paper, we present a Web-based demo application that automatically quantifies the cross-modal relations of entities (persons, locations, and events) in image and text. The applications are manifold. For example, the system can help users to explore multimodal articles more efficiently, or can assist human assessors and fact-checking efforts in the verification of the credibility of news stories, tweets, or other multimodal documents.

中文翻译：

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QuTI！量化多模式文档中的文本图像一致性

万维网和社交媒体平台已成为新闻和信息的流行来源。通常，多模态信息（例如图像和文本）用于更有效地传达信息并引起注意。尽管在大多数情况下，图像内容是装饰性的或描绘了其他信息，但近年来，也利用它来传播错误信息和谣言。在本文中，我们提出了一个基于Web的演示应用程序，该应用程序自动量化图像和文本中实体（人，位置和事件）的交叉模式关系。应用是多种多样的。例如，该系统可以帮助用户更有效地浏览多模式文章，或者可以协助人类评估人员和事实检查工作来验证新闻故事，推文或其他多模式文档的可信度。