Aligned Multi-View Scripts for Universal Chart-to-Code Generation
Chart-to-code generation converts a chart image into an executable plotting script, enabling faithful reproduction and editable visualizations. Existing methods are largely Python-centric, limiting practical use and overlooking a critical source of supervision: the same chart can be expressed by semantically equivalent scripts in different plotting languages. To fill this gap, we introduce Chart2NCode, a dataset of 176K charts paired with aligned scripts in Python, R, and LaTeX that render visually equivalent outputs, constructed via a metadata-to-template pipeline with rendering verification and human quality checks. Building on a LLaVA-style architecture, we further propose CharLuMA, a ...
| Authors | Zhihan Zhang, Lizi Liao |
|---|---|
| Primary category | cs.CL |
| Published | 27 April 2026 |
| Last updated at source | 27 April 2026 |
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