3 papers
cs.LG2025
Addressing divergent representations from causal interventions on neural networks
Satchel Grant, Simon Jerome Han, Alexa R. Tartaglini +1
A common approach to mechanistic interpretability is to causally manipulate model representations via targeted interventions in order to understand what those representations encod…
cs.CV2025
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…
cs.HC2025
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…