AI 中文总结
Flint是一种语义驱动的数据可视化中间语言，通过分层数据语义模型，让作者从简洁规范创建高质量可视化，能生成并优化与库无关的配置，转化为多目标语法的可执行规范，简化创作过程且不损视觉质量。
AI 中文摘要
我们展示了Flint，一种中间语言，它能让作者从简洁的、语义驱动的规范中创建高质量可视化，而无需明确配置诸如比例、轴和格式等低级参数。与以往从表面数据表示推断默认配置（常产生脆弱选择）的系统不同，Flint引入分层数据语义模型，助用户结构化指定数据字段含义，帮编译器得出合适可视化配置。系统从简洁规范生成并优化与库无关的可视化配置，转化为针对多种目标语法的完整可执行规范。我们证明Flint简化创作过程且不损视觉质量，对人类和人工智能代理创建可视化都是有效中间语言。
英文摘要
We present Flint, an intermediate language that enables authors to create high-quality visualizations from concise, semantics-driven specifications without explicitly configuring low-level parameters such as scales, axes, and formatting. Unlike prior systems that infer default configurations from surface-level data representations, often producing brittle choices, Flint introduces a hierarchical data semantic model that allows users to specify the meanings of data fields structurally and helps the compiler derive appropriate visualization configurations. From a concise specification, the system generates and optimizes library-agnostic visualization configurations and translates them into complete, executable specifications for multiple target grammars, including Vega-Lite, Apache ECharts, and Chart.js. We demonstrate that Flint simplifies the authoring process without compromising on visual quality, and it is an effective intermediate language for both humans and AI agents to create visualizations.
