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No single large model dominates in parametric CAD modeling, revealing significant trade-offs in executability and visual-semantic identity.
Treating robot skill calls as runtime-verified execution proposals rather than blind action predictions enables self-correcting VLA autonomy that reaches 97.4% success on LIBERO.
