用GUI代理自动化电子设计流程，首次实现超越博士生的工程表现。
Using GUI Agent for Electronic Design Automation
- 构建专用数据集GUI-EDA，涵盖5类工具和2000+真实设计任务对。
- 提出EDA特殊评估指标EDAgent，首次在工业软件中超越电气工程博士生。
- 揭示现有代理在专业电子设计领域性能严重不足，为工程自动化提供新方向。
图形用户界面（GUI）代理采用端到端范式，将屏幕截图映射为操作序列，从而自动化虚拟环境中的重复任务。然而，现有GUI代理几乎仅在Word、Excel等通用软件上评估。专业计算机辅助设计（CAD）套件带来的经济回报高一个数量级，但仍是现有代理表现最弱的领域，远未取代电子设计自动化（EDA）工程师。本文首次系统研究GUI代理在EDA工作流中的应用：(1) 构建大规模数据集GUI-EDA，包含5种CAD工具和5个物理领域，涵盖2000多个由EDA科学家和工程师在真实组件设计中记录的高质量截图-答案-操作对；(2) 设计全面基准，评估30余种主流GUI代理，证明EDA任务构成重大且未解决的挑战；(3) 提出专用于EDA的评估指标EDAgent，配备反思机制，在工业级CAD软件上实现可靠性能，并首次超越电气工程专业博士生水平。本工作将GUI代理从通用办公自动化拓展至高价值专业工程领域，为提升EDA生产效率开辟新路径。数据集将开源：https://github.com/aiben-ch/GUI-EDA。
原文摘要 · Abstract (English)
Graphical User Interface (GUI) agents adopt an end-to-end paradigm that maps a screenshot to an action sequence, thereby automating repetitive tasks in virtual environments. However, existing GUI agents are evaluated almost exclusively on commodity software such as Microsoft Word and Excel. Professional Computer-Aided Design (CAD) suites promise an order-of-magnitude higher economic return, yet remain the weakest performance domain for existing agents and are still far from replacing expert Electronic-Design-Automation (EDA) engineers. We therefore present the first systematic study that deploys GUI agents for EDA workflows. Our contributions are: (1) a large-scale dataset named GUI-EDA, including 5 CAD tools and 5 physical domains, comprising 2,000+ high-quality screenshot-answer-action pairs recorded by EDA scientists and engineers during real-world component design; (2) a comprehensive benchmark that evaluates 30+ mainstream GUI agents, demonstrating that EDA tasks constitute a major, unsolved challenge; and (3) an EDA-specialized metric named EDAgent, equipped with a reflection mechanism that achieves reliable performance on industrial CAD software and, for the first time, outperforms Ph.D. students majored in Electrical Engineering. This work extends GUI agents from generic office automation to specialized, high-value engineering domains and offers a new avenue for advancing EDA productivity. The dataset will be released at: https://github.com/aiben-ch/GUI-EDA.
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