CAD-Coder generates valid CadQuery scripts from text via supervised fine-tuning followed by reinforcement learning with geometric Chamfer Distance rewards and chain-of-thought planning.
Fusion 360 gallery: A dataset and environment for programmatic cad construction from human design sequences.ACM Transactions on Graphics (TOG), 40(4):1–24
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
dataset 1
citation-polarity summary
roles
dataset 1polarities
use dataset 1representative citing papers
CADBench is a multimodal benchmark for CAD program generation that shows specialized mesh-to-CAD models outperform general vision-language models but degrade with complexity and modality shifts.
CAD agents using finite element analysis feedback plus new text blueprint and multi-view image signals improve geometric accuracy on S2O and Fusion360 benchmarks while addressing physical validity gaps in prior generation methods.
citing papers explorer
-
CAD-Coder: Text-to-CAD Generation with Chain-of-Thought and Geometric Reward
CAD-Coder generates valid CadQuery scripts from text via supervised fine-tuning followed by reinforcement learning with geometric Chamfer Distance rewards and chain-of-thought planning.
-
CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation
CADBench is a multimodal benchmark for CAD program generation that shows specialized mesh-to-CAD models outperform general vision-language models but degrade with complexity and modality shifts.
-
Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback
CAD agents using finite element analysis feedback plus new text blueprint and multi-view image signals improve geometric accuracy on S2O and Fusion360 benchmarks while addressing physical validity gaps in prior generation methods.