Dashboard2Code: Evaluating Multimodal Models on Reconstructing Interactive Dashboards
Automatic data visualization generation has advanced rapidly with multi-modal large language models, yet existing efforts largely focus on static charts and overlook the interactive dashboards commonly used for real-world data exploration. We introduce Dashboard2Code, a novel task that requires a model to proactively explore an interactive dashboard, acquire and integrate feedback from its own interactions (e.g., clicking and filtering), and generate code that reproduces the target dashboard. To support comprehensive evaluation, we present DashboardMimic, the first Plotly+Dash benchmark for Dashboard2Code, comprising 180 carefully designed and manually verified dashboard-code pairs spanni...
| Authors | Tianhao Niu, Ziyu Han, Qiguang Chen et al. |
|---|---|
| Primary category | cs.SE |
| Published | 6 July 2026 |
| Last updated at source | 6 July 2026 |
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