Johns Hopkins researchers introduce ALIGN-Parts, a novel AI model that predicts named 3D object components by aligning geometric segmentation with natural language descriptions. The approach solves dual challenges of segmenting parts and assigning consistent semantic labels through a set-to-set alignment framework, enabling applications from robotics to 3D content creation.