papersSEP 12 04:00 UTC
Paper Proposes Language-Augmented Priors for B-Spline Surface Fitting
A new arXiv preprint describes a technique that uses language-derived semantic information to guide B-spline and NURBS surface fitting, the mathematical basis of modern computer-aided design. The authors argue that traditional CAD geometric kernels remain dependent on predefined assumptions, and that language-augmented priors can improve fitting results. The work sits at the intersection of geometric modeling and language model research.