让文字直接生成可编辑的3D设计代码，提升工业级可修改性。
Arko-T: A Foundation Model for Text-to-Structured 3D Generation
- 将自然语言转为可执行的参数化CAD程序，保留设计逻辑。
- 在12项指标中8项领先，成本仅为同类模型的十分之一。
- 适合需要可编辑3D设计的工程师与设计师使用。
文本到3D系统如今能仅凭一句话生成可渲染的模型，但结果难以编辑。我们提出Arko-T，一个40亿参数的文本到设计模型，可将自然语言意图直接映射为可执行的参数化CAD程序。不同于仅优化代码可执行性，Arko-T在整个流程中对齐形式化的设计状态，使数据整理、代码规范化和执行监督均致力于保留特征、参数与构建逻辑，以保障CAD成果的可编辑性。在12项指标上对比7个前沿大模型，Arko-T在8项中排名第一，3项第二，且每项基准成本仅为十分之一。结果表明，在适度规模下进行针对性设计训练，可媲美顶尖通用模型在结构化CAD生成上的表现。
原文摘要 · Abstract (English)
Text-to-3D systems can now synthesize a model from a single sentence, yet the result is a shape to render, not a design to edit. We present Arko-T, a 4B-parameter text-to-design model that maps natural-language intent directly into executable, parametric CAD programs. Rather than optimizing for code executability alone, Arko-T aligns every stage of the pipeline to a formal notion of design state, so that data curation, code normalization, and execution-grounded supervision all work to preserve the features, parameters, and construction logic that make a CAD artifact editable. Benchmarked against seven frontier LLMs across 12 metrics, Arko-T attains the best score on 8 and the second-best on 3 more, at roughly one-tenth the per-benchmark cost. The results suggest that targeted design-level training at moderate scale can match frontier general-purpose models on structured CAD generation.
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