Accelerating Scientific Paper Skimming with Augmented Intelligence Through Customizable Faceted Highlights

• Published in: ACM transactions on interactive intelligent systems 2024-12, Vol.14 (4), p.1-30, Article 27
• Main Authors: Fok, Raymond, Soldaini, Luca, Trier, Cassidy, Bransom, Erin, MacMillan, Kelsey, Cheng, Evie, Kambhamettu, Hita, Bragg, Jonathan, Lo, Kyle, Hearst, Marti A., Head, Andrew, Weld, Daniel S.
• Format: Article
• Language: English
• Subjects: Empirical studies in HCI; Human-centered computing; Interactive systems and tools
• ISSN: 2160-6455; 2160-6463
• DOI: 10.1145/3665648

Scholars need to keep up with an exponentially increasing flood of scientific papers. To aid this challenge, we introduce Scim, a novel intelligent interface that helps scholars skim papers to rapidly review and gain a cursory understanding of its contents. Scim supports the skimming process by highlighting salient content within a paper, directing a scholar’s attention. These automatically-extracted highlights are faceted by content type, evenly-distributed across a paper, and have a density configurable by scholars. We evaluate Scim with an in-lab usability study and a longitudinal diary study, revealing how its highlights facilitate the more efficient construction of a conceptualization of a paper. Finally, we describe the process of scaling highlights from their conception within Scim, a research prototype, to production on over 521,000 papers within the Semantic Reader, a publicly-available augmented reading interface for scientific papers. We conclude by discussing design considerations and tensions for the design of future skimming tools with augmented intelligence.