arXiv:2605. 28579v2 Announce Type: replace Abstract: Large language models (LLMs) have recently advanced text-driven 3D generation, yet Text-to-CAD remains far from supporting industrial product design.
By Xiaoyu Dong, Zhi Li, Xiao-Ming Wu
VisCAD is a foundation model suite that tackles AI-assisted computer-aided design for industrial products, covering both part-level and assembly-level generation. Its core component, VisCAD‑M1, is a 27B model trained for part-level design generation and outperforms existing models on PubCADBench and RealCADBench, achieving a part-level score of 0.5540 and reaching 0.5797 when used as a test-time verifier. VisCAD also offers a domain-specific harness that improves complex assembly generation compared to general-purpose harnesses, showing quantitative and qualitative advantages.
By JoyIndustrial VisCAD Team, Linxin Cai, Qiuhe Hong, Zhichao Huang, Guanlin Li, Hongsen Liu, Ziqi Liu, Yichen Long, Luya Wang, Yuchen Wang, Wenxiang Wu, Huimu Yu, Ning Zhang
CADKnitter is a compositional CAD generation framework that uses geometric-guiding cues to steer diffusion sampling, enabling the creation of complementary CAD parts that satisfy both geometric constraints of an existing model and semantic constraints from a text prompt. The authors introduce KnitCAD, a dataset of over 310,000 CAD models paired with textual prompts and assembly metadata to support training and evaluation. Experiments show that CADKnitter outperforms state‑of‑the‑art baselines by a clear margin.
By Tri Le, Khang Nguyen, Baoru Huang, Tung D. Ta, Anh Nguyen
arXiv:2609.07434v1 Announce Type: new
Abstract: Natural-language Computer-Aided Design (CAD) code generation aims to turn design intent into executable and editable parametric programs. Large languag...
By Yali Du, Hui Sun, San-Zhuo Xi, Ming Li
arXiv:2608.28669v1 Announce Type: new
Abstract: Recovering an executable parametric CAD program from an observed object is fundamentally ambiguous, because the same final geometry can result from dif...
By Jizong Zhan
arXiv:2608. 05714v1 Announce Type: new Abstract: Text-to-CAD generation translates natural-language design intent into editable and executable parametric computer-aided design (CAD) codes, reducing the expertise and effort required for manual modeling.
By Shuhao Yan, Changhao He, Xi Peng, Peng Hu
arXiv:2607. 05573v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) and Vision-Language Models (VLMs) enable the automatic generation of parametric 3D designs from natural-language specifications.
By J de Curt\`o, Victoria Guill\'en, I. de Zarz\`a
arXiv:2603. 05607v2 Announce Type: replace-cross Abstract: Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by small annotated datasets with explicit design histories or boundary representation (BRep) labels.
By Mohammad Sadil Khan, Muhammad Usama, Rolandos Alexandros Potamias, Didier Stricker, Muhammad Zeshan Afzal, Jiankang Deng, Ismail Elezi
arXiv:2606. 20146v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to computer-aided design (CAD) to generate design artifacts from textual instructions.
By Bharathi Kannan Nithyanantham, Clemens Kujat, Tobias Sesterhenn, Stefan Telgmann, J\"orn Pl\"onnigs, Stefan L\"udtke, Christian Bartelt
arXiv:2602. 03045v2 Announce Type: replace Abstract: Large language models have recently enabled text-to-CAD systems that synthesize parametric CAD programs (e.
By Bo Yuan, Zelin Zhao, Petr Molodyk, Bin Hu, Yongxin Chen
arXiv:2606. 31252v1 Announce Type: new Abstract: Large language models can write plausible CAD scripts, but reliable industrial CAD modeling requires more than syntactically valid code: every feature, placement, and assembly relation must be accepted by an exact geometric kernel while remaining editable as parametric boundary representation geometry.
By Fumin Liu, Haoyu Zhou, Fei Hao, Lin Yang
arXiv:2607. 05123v1 Announce Type: new Abstract: Recent advances in large language models and programmatic CAD have significantly improved Text-to-CAD generation for individual parts.
By Yurui Dong, Shu Zou, Siqi Li, Nianchen Deng, Hongbin Zhou, Xuemeng Yang, Pinlong Cai, Licheng Wen, Xinyu Cai, Botian Shi