1 citations · 3 across the 6 of their papers we have counts for
7 papers
Draw it like Euclid: Teaching transformer models to generate CAD profiles using ruler and compass construction steps
Siyi Li, Joseph G. Lambourne, Longfei Zhang +2
We introduce a new method of generating Computer Aided Design (CAD) profiles via a sequence of simple geometric constructions including curve offsetting, rotations and intersection…
mrCAD: Multimodal Refinement of Computer-aided Designs
William P. McCarthy, Saujas Vaduguru, Karl D. D. Willis +4
A key feature of human collaboration is the ability to iteratively refine the concepts we have communicated. In contrast, while generative AI excels at the \textit{generation} of c…
Aligning Constraint Generation with Design Intent in Parametric CAD
Evan Casey, Tianyu Zhang, Shu Ishida +6
We adapt alignment techniques from reasoning LLMs to the task of generating engineering sketch constraints found in computer-aided design (CAD) models. Engineering sketches consist…
CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketches
Sifan Wu, Amir Khasahmadi, Mor Katz +4
Parametric Computer-Aided Design (CAD) is central to contemporary mechanical design. However, it encounters challenges in achieving precise parametric sketch modeling and lacks pra…
Creating Language-driven Spatial Variations of Icon Images
Xianghao Xu, Aditya Ganeshan, Karl D. D. Willis +2
Editing 2D icon images can require significant manual effort from designers. It involves manipulating multiple geometries while maintaining the logical or physical coherence of the…
ASAP: Automated Sequence Planning for Complex Robotic Assembly with Physical Feasibility
Yunsheng Tian, Karl D. D. Willis, Bassel Al Omari +10
The automated assembly of complex products requires a system that can automatically plan a physically feasible sequence of actions for assembling many parts together. In this paper…
TExplain: Explaining Learned Visual Features via Pre-trained (Frozen) Language Models
Saeid Asgari Taghanaki, Aliasghar Khani, Ali Saheb Pasand +4
Interpreting the learned features of vision models has posed a longstanding challenge in the field of machine learning. To address this issue, we propose a novel method that levera…