Data tables play a central role in scientific papers. However, their meaning is often co-constructed with surrounding text through narrative interplay, making comprehension cognitively demanding for readers. In this work, we explore how interfaces can better support this reading process. We conducted a formative study that revealed key characteristics of text-table narrative interplay, including linking mechanisms, multi-granularity alignments, and mention typologies, as well as a layered framework of readers' intents. Informed by these insights, we present TableTale, an augmented reading interface that enriches text with data tables at multiple granularities, including paragraphs, sentences, and mentions. TableTale automatically constructs a document-level linking schema within the paper and progressively renders cascade visual cues on text and tables that unfold as readers move through the text. A within-subject study with 24 participants showed that TableTale reduced cognitive workload and improved reading efficiency, demonstrating its potential to enhance paper reading and inform future reading interface design.

翻译：数据表格在科学论文中扮演着核心角色。然而，其意义往往通过与周围文本的叙事交互共同构建，这给读者的理解带来了较高的认知负荷。在本工作中，我们探讨了界面如何能更好地支持这一阅读过程。我们开展了一项形成性研究，揭示了文本-表格叙事交互的关键特征，包括链接机制、多粒度对齐及提及类型，以及读者意图的层级框架。基于这些洞见，我们提出了TableTale——一种增强型阅读界面，它在多个粒度（包括段落、句子和提及）上为文本丰富了数据表格。TableTale能在论文内部自动构建文档级的链接模式，并随着读者在文本中的阅读进程，渐进式地在文本和表格上渲染级联视觉线索。一项包含24名参与者的受试者内研究表明，TableTale降低了认知负荷并提升了阅读效率，证明了其在增强论文阅读体验和为未来阅读界面设计提供参考方面的潜力。