SOURCE-LINKED INTELLIGENCE
Object-Centric Conditioning for Visuomotor Flow Matching
Robot visuomotor policies are commonly formulated as autoregressive, diffusion-based, or more recently, flow matching models. Among them, Action-to-Action (A2A) flow matching improves inference efficiency by initializing generation from historical action priors rather than stochastic noise. However, stale historical motion patterns and entangled global visual representations can jointly reduce robustness under spatial out-of-distribution (OOD) shifts and visual distractors. In this work, we propose SlotFlow, an object-centric flow matching policy for robust visuomotor manipulation. SlotFlow de
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-21T06:14:34.000Z
First collected: 2026-09-23T08:01:43.213Z. This is not the publication date.