CADFather coordinates learned, geometric, and optimization tools through a vision-language assistant, reaching zero invalid outputs across six CAD reconstruction benchmarks
CADFather is an autonomous, training-free agent in which a vision-language assistant decides which candidate CAD program to extend, which tool to invoke, and how many proposals to sample, unifying learned proposal generation, geometry-based algorithmic proposals, and parameter optimization in one CadQuery representation, and achieving zero invalidity with higher mean IoU and GMS and lower median Chamfer distance on the full DeepCAD, Fusion360, and MCB test sets.