
Exploring the Capability of LLMs in Performing Low-Level Visual Analytic Tasks on SVG Data Visualizations
Data visualizations help extract insights from datasets, but reaching these insights requires decomposing high level goals into low-level analytic tasks that can be complex due to varying degrees of data literacy and visualization experience. This research explores how large language models can perform visual analytic tasks directly on SVG-based visualizations.