4 citations · 4 across the 5 of their papers we have counts for
5 papers
Diagnosing Bottlenecks in Data Visualization Understanding by Vision-Language Models
Alexa R. Tartaglini, Satchel Grant, Daniel Wurgaft +2
Data visualizations are vital components of many scientific articles and news stories. Current vision-language models (VLMs) still struggle on basic data visualization understandin…
Human-centered evaluation of data visualization understanding in vision-language models
Arnav Verma, Kushin Mukherjee, Christopher Potts +2
Data visualization understanding, which requires integrating visual, numerical, and linguistic inputs, poses fundamental challenges to multimodal reasoning. Recently developed visi…
Measuring and predicting variation in the difficulty of questions about data visualizations
Arnav Verma, Judith E. Fan
Understanding what is communicated by data visualizations is a critical component of scientific literacy in the modern era. However, it remains unclear why some tasks involving dat…
SEVA: Leveraging sketches to evaluate alignment between human and machine visual abstraction
Kushin Mukherjee, Holly Huey, Xuanchen Lu +4
Sketching is a powerful tool for creating abstract images that are sparse but meaningful. Sketch understanding poses fundamental challenges for general-purpose vision algorithms be…
Open Vocabulary Semantic Scene Sketch Understanding
Ahmed Bourouis, Judith Ellen Fan, Yulia Gryaditskaya
We study the underexplored but fundamental vision problem of machine understanding of abstract freehand scene sketches. We introduce a sketch encoder that results in semantically-a…