Jing Chen

Dynamic feature fusion for lightweight material recommendation in CAD assemblies

A lightweight feature-embedding framework for node-level material prediction in CAD assemblies that projects semantic, geometric, and physical component descriptors into an expanded embedding space, concatenates the learned embedding with the original descriptors, and uses a zero-initialized adaptive residual branch to control low-level feature supplementation during training.