More Structure, Not More Capacity: Object-Centric Representations for Visuomotor Imitation Learning

arXiv:2607.09825v1 Announce Type: new Abstract: Robotic manipulation policies rely on pre-trained vision models that give either a global scene embedding or a dense patch grid. Both mix task-relevant and task-irrelevant features. Object-centric slot representations are a structured alternative: they group features into a few per-object slots. We test what this structure buys on ManiSkill3 PickCube-v1, with a frozen encoder and a held-out-seed evaluation. Holding the policy, goal token, rendering...