Large Language Models for Computer-Aided Design: A Survey

May 13, 2025 ยท Declared Dead ยท ๐Ÿ› ACM Computing Surveys

๐Ÿฆด CAUSE OF DEATH: Skeleton Repo
Boilerplate only, no real code

Repo contents: README.md, taxonomy.png

Authors Licheng Zhang, Bach Le, Naveed Akhtar, Siew-Kei Lam, Tuan Ngo arXiv ID 2505.08137 Category cs.LG: Machine Learning Cross-listed cs.CL, cs.GR, cs.MM Citations 11 Venue ACM Computing Surveys Repository https://github.com/lichengzhanguom/LLMs-CAD-Survey-Taxonomy โญ 32 Last Checked 2 months ago
Abstract
Large Language Models (LLMs) have seen rapid advancements in recent years, with models like ChatGPT and DeepSeek, showcasing their remarkable capabilities across diverse domains. While substantial research has been conducted on LLMs in various fields, a comprehensive review focusing on their integration with Computer-Aided Design (CAD) remains notably absent. CAD is the industry standard for 3D modeling and plays a vital role in the design and development of products across different industries. As the complexity of modern designs increases, the potential for LLMs to enhance and streamline CAD workflows presents an exciting frontier. This article presents the first systematic survey exploring the intersection of LLMs and CAD. We begin by outlining the industrial significance of CAD, highlighting the need for AI-driven innovation. Next, we provide a detailed overview of the foundation of LLMs. We also examine both closed-source LLMs as well as publicly available models. The core of this review focuses on the various applications of LLMs in CAD, providing a taxonomy of six key areas where these models are making considerable impact. Finally, we propose several promising future directions for further advancements, which offer vast opportunities for innovation and are poised to shape the future of CAD technology. Github: https://github.com/lichengzhanguom/LLMs-CAD-Survey-Taxonomy
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

๐Ÿ“œ Similar Papers

In the same crypt โ€” Machine Learning

Died the same way โ€” ๐Ÿฆด Skeleton Repo

R.I.P. ๐Ÿฆด Skeleton Repo

Neural Style Transfer: A Review

Yongcheng Jing, Yezhou Yang, ... (+4 more)

cs.CV ๐Ÿ› IEEE TVCG ๐Ÿ“š 828 cites 8 years ago