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
arXiv:2608.00800v2 Announce Type: replace
Abstract: Injection molding is the cornerstone of mass-producing plastic components. While current algorithms can automate mold design for basic geometries u...
By Pengyun Qiu, Shuo Wang, Zeyuan Chen, Yihao Zhi, Chongjie Ye, Xiaoguang Han
arXiv:2602. 00072v2 Announce Type: replace Abstract: The performance of machine learning surrogates is critically dependent on data quality and quantity.
By Jice Zeng, David Barajas-Solano, Hui Chen
arXiv:2605. 01171v2 Announce Type: replace-cross Abstract: Despite recent progress, recovering parametric CAD construction sequences from geometric input, such as meshes or point clouds, is a key challenge for design and manufacturing, as existing CAD reconstruction and generation methods are largely restricted to difficult-to-edit formats like meshes or Breps or editable simple sketch-and-extrude pipelines and low-complexity datasets.
By Ghadi Nehme, Eamon Whalen, Faez Ahmed
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:2606. 05058v1 Announce Type: cross Abstract: Computer-Aided Design (CAD) underpins modern engineering and manufacturing by enabling the creation of precise, editable 3D models.
By Jingyuan Chen, Sheng Jin, Haopeng Sun, Wentao Liu, Chen Qian