Can Li

DeformSmith presents a hierarchical agentic framework that, from text or a single image, progressively builds geometry, a physical model, material behavior, and robot interaction, using a shared physics-grounded harness to evaluate and revise candidates through simulation probes and robot pick-and-place feedback; across 39 cases its assets score higher on visual quality and physical plausibility than baselines including PhysGen3D, PhysGM, and PhysX-Omni, while also producing replayable manipulation data.

DeformSmith presents a hierarchical agentic framework that, from text or a single image, progressively builds geometry, a physical model, material behavior, and robot interaction, using a shared physics-grounded harness to evaluate and revise candidates through simulation probes and robot pick-and-place feedback; across 39 cases its assets score higher on visual quality and physical plausibility than baselines including PhysGen3D, PhysGM, and PhysX-Omni, while also producing replayable manipulation data.