3 papers
cs.AI2026
TraceCAD: Trace-Guided Repair for Agentic CAD Generation
Fengxiao Fan, Jingzhe Ni, Fan Sang +5
LLM-based CAD agents produce executable parametric programs, but their correction loops may lose evidence about satisfied requirements, faulty operations, and prior repairs. We int…
cs.AI2026
CADIR: A Cross-Backend Editable Intermediate Representation for Agentic CAD Generation
Yu Liu, Jingzhe Ni, Yiming Chen +4
Large language models have made it possible to generate executable computer-aided design (CAD) programs from natural-language descriptions or images. However, existing methods repr…
cs.LG2025
RLCAD: Reinforcement Learning Training Gym for Revolution Involved CAD Command Sequence Generation
Xiaolong Yin, Xingyu Lu, Jiahang Shen +5
A CAD command sequence is a typical parametric design paradigm in 3D CAD systems where a model is constructed by overlaying 2D sketches with operations such as extrusion, revolutio…