61 citations · 131 across the 8 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.HC2023
Never-ending Learning of User Interfaces
Jason Wu, Rebecca Krosnick, Eldon Schoop +3
Machine learning models have been trained to predict semantic information about user interfaces (UIs) to make apps more accessible, easier to test, and to automate. Currently, most…
cs.HC2023
WebUI: A Dataset for Enhancing Visual UI Understanding with Web Semantics
Jason Wu, Siyan Wang, Siman Shen +3
Modeling user interfaces (UIs) from visual information allows systems to make inferences about the functionality and semantics needed to support use cases in accessibility, app aut…
cs.HC2023★ 3 cited
Screen Correspondence: Mapping Interchangeable Elements between UIs
Jason Wu, Amanda Swearngin, Xiaoyi Zhang +2
Understanding user interface (UI) functionality is a useful yet challenging task for both machines and people. In this paper, we investigate a machine learning approach for screen…