SOURCE-LINKED INTELLIGENCE

Chart2SVG: Editable SVG Generation from Raster Chart Images

arXiv · AI, language, vision and robotics · article · Aug 27, 2026 · UTC

We present Chart2SVG, a multimodal large language model that converts static raster charts into structurally organized, semantically enriched SVGs that support programmatic editing. By incorporating chart-specific semantic tokens into a vision-language model, Chart2SVG captures both geometric primitives and their functional roles. To support robust structural recovery, we introduce Beagle+, a dataset of 33K canonicalized and structurally distilled chart samples. Our approach combines specialized training objectives with a rendering-aware post-training phase, producing SVGs that are both visual

Read original source ↗ Open in workspace

recordType

paper

region

Global