发表机构
DEIB Politecnico di Milano（米兰理工大学DEIB）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出Inspector框架，结合微调LLM与CNN分析模拟电路GDSII文件，提供对话式界面，在四个实际任务中较通用大规模VLM最高提升81%，实现轻量级分析。
AI 中文摘要
人工智能与计算机辅助设计框架的集成引发了模拟集成电路（IC）设计领域的转变，使该领域从使用手动和基于算法的解决方案转向采用自动化和智能范式。在此背景下，GDSII文件作为行业标准数据库，包含模拟电路最终且最准确的信息来源，封装了决定流片性能的复杂物理几何和寄生现实。本文提出了一种新颖框架，结合微调后的LLM和CNN来分析模拟电路的GDSII文件，实现工具与设计者之间的对话式界面。在四个实际任务中使用数千个模拟设计的实验结果表明，所提出的解决方案显著优于最先进的通用大规模VLM（最高提升81%），从而为GDSII分析问题提供了轻量级解决方案。
英文摘要
The integration of artificial intelligence into computer-aided design frameworks has sparked a shift in the design of analog integrated circuits (ICs), transitioning the field from using manual and algorithmic-based solutions to adopting automated and intelligent paradigms. In this scenario, the GDSII file represents the industry-standard database containing the ultimate and most accurate source of information of the analog circuit, encapsulating the complex physical geometries and parasitic realities that define tape out performance. This paper proposes a novel framework that combines fine-tuned LLMs and CNNs to analyze GDSII files of analog circuits, enabling a conversational interface between the tool and the designers. Experimental results using thousands of analog designs across four realistic tasks demonstrate that the proposed solution outperforms state-of-the-art general-purpose massive VLMs by a significant margin (up to 81%), thus providing a lightweight solution to the problem of GDSII analysis.
Comments4 pages, 5 figures, 5 tables, to be published in ICLAD 2026
