6 papers
BrepLLM: Enabling Large Language Models to Understand Boundary Representations
Liyuan Deng, Hao Guo, Yongkang Dai +5
Current token-sequence-based Large Language Models (LLMs) struggle to directly process 3D Boundary Representation (B-rep) models that contain complex geometric and topological info…
COSMO-Agent: Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration
Liyuan Deng, Shujian Deng, Yongkang Chen +6
Iterative industrial design-simulation optimization is bottlenecked by the CAD-CAE semantic gap: translating simulation feedback into valid geometric edits under diverse, coupled c…
Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration
Liyuan Deng, Shujian Deng, Yongkang Chen +6
Iterative industrial design-simulation optimization is bottlenecked by the CAD-CAE semantic gap: translating simulation feedback into valid geometric edits under diverse, coupled c…
AutoRegressive Generation with B-rep Holistic Token Sequence Representation
Jiahao Li, Yunpeng Bai, Yongkang Dai +3
Previous representation and generation approaches for the B-rep relied on graph-based representations that disentangle geometric and topological features through decoupled computat…
MamTiff-CAD: Multi-Scale Latent Diffusion with Mamba+ for Complex Parametric Sequence
Liyuan Deng, Yunpeng Bai, Yongkang Dai +5
Parametric Computer-Aided Design (CAD) is crucial in industrial applications, yet existing approaches often struggle to generate long sequence parametric commands due to complex CA…
BRepFormer: Transformer-Based B-rep Geometric Feature Recognition
Yongkang Dai, Xiaoshui Huang, Yunpeng Bai +4
Recognizing geometric features on B-rep models is a cornerstone technique for multimedia content-based retrieval and has been widely applied in intelligent manufacturing. However,…