6 papers
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…
OpenClawBench: Benchmarking Process-side Anomalies in Real-world Agent Execution Trajectories
Yibing Liu, Yangze Liu, Xiaolong Yin +4
Task success can hide process anomalies in real-world agent executions. An agent may pass the final task oracle while still accumulating unresolved ambiguity, unsafe external write…
Memory-Augmented Reinforcement Learning Agent for CAD Generation
Yin Xiaolong, Liu Yu, Shen Jiahang +4
Automatic generation of computer-aided design (CAD) models is a core technology for enabling intelligence in advanced manufacturing. Existing generation methods based on large lang…
CADDesigner: Conceptual CAD Model Generation with a General-Purpose Agent
Fengxiao Fan, Jingzhe Ni, Xiaolong Yin +6
Computer-Aided Design (CAD) is widely used for conceptual design and parametric 3D modeling, but typically requires a high level of expertise from designers. To lower the entry bar…
Img2CADSeq: Image-to-CAD Generation via Sequence-Based Diffusion
Shiyu Tan, Zixuan Zhao, Hao Gao +3
Boundary Representation (BRep) is the standard format for Computer-Aided Design (CAD), yet reconstructing high-quality BReps from single-view images remains challenging due to the…
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…