9 papers
ArtisanCAD: An Industrial-Level CAD Agent with Expert-Grounded Knowledge Distillation
Yunhan Xu, Qifeng Wu, Xunjin Li +10
Computer-aided design (CAD) for industrial components requires long-horizon procedural modeling, robust feature dependencies, editable parametric geometry, and production-grade B-R…
Knowledge-Constrained Shape Optimization with a Mixture-of-Experts Neural Operator for High-Confidence Design
Wenhao Fan, Yuanwei Bin, Jianghan Gu +4
Engineering shape optimization faces challenges in both expert-dependent problem setup and surrogate-model reliability. In practical aerodynamic design, optimization settings such…
Least-Action-Guided Diffusion for Physical Extrapolation
Zhongxin Yang, Yuanwei Bin, Xiang I. A. Yang +1
Reliable extrapolation remains a central challenge for generative models in computational physics, because models trained over finite ranges of time, parameters, or geometries may…
Turbulence-like 5/3 spectral scaling in contextual representations of language as a complex system
Zhongxin Yang, Chun Bao, Yuanwei Bin +2
Natural language is a complex system that exhibits robust statistical regularities. Here, we represent text as a trajectory in a high-dimensional embedding space generated by trans…
LawMind: A Law-Driven Paradigm for Discovering Analytical Solutions to Partial Differential Equations
Min-Yi Zheng, Shengqi Zhang, Liancheng Wu +3
Partial differential equations (PDEs) encode fundamental physical laws, yet closed-form analytical solutions for many important equations remain unknown and typically require subst…
An explainable operator approximation framework under the guideline of Green's function
Jianghang Gu, Ling Wen, Yuntian Chen +1
Traditional numerical methods, such as the finite element method and finite volume method, adress partial differential equations (PDEs) by discretizing them into algebraic equation…