用可执行测试评估文本生成CAD模型，提升设计自动化水平。
Text-to-CAD Evaluation with CADTests
- 基于可执行测试构建首个文本转CAD评测基准。
- 测试验证生成模型是否满足几何与拓扑要求，性能更可靠。
- 适合关注CAD生成与自动化设计的研究者和工程师。
文本转CAD作为新兴重要任务，有望显著加速设计流程。然而，相关评估研究仍非常匮乏，模型生成性能的评估仍面临挑战。本文提出基于自动化测试的全新评估视角，引入CADTestBench——首个基于CADTests（可执行软件测试）的文本转CAD评测基准，用于验证生成的CAD模型是否满足输入提示中的几何与拓扑要求。通过该基准，我们对近期文本转CAD方法进行了全面评估，并进一步证明CADTests可引导模型生成，构建出超越当前主流方法的简单基线。代码与数据已开源至GitHub与Hugging Face数据集。
原文摘要 · Abstract (English)
Text-to-CAD has recently emerged as an important task with the potential to substantially accelerate design workflows. Despite its significance, there has been surprisingly little work on Text-to-CAD evaluation, and assessing CAD model generation performance remains a considerable challenge. In this work, we introduce a new evaluation perspective for Text-to-CAD based on automated testing. We propose CADTestBench, the first test-based benchmark for Text-to-CAD, based on CADTests, executable software tests that verify whether a generated CAD model satisfies the geometric and topological requirements of the input prompt. Using CADTestBench, we conduct comprehensive benchmarking of recent Text-to-CAD methods and further demonstrate that CADTests can also guide CAD model generation, yielding simple baselines that surpass performance of current methods. CADTestBench code and data are available at GitHub and Hugging Face dataset.
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