AIBullisharXiv – CS AI · 10h ago7/10
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LoopVLA: Learning Sufficiency in Recurrent Refinement for Vision-Language-Action Models
LoopVLA introduces a recurrent Vision-Language-Action model architecture that learns when to stop refining representations for robotic control tasks, achieving 45% parameter reduction and 1.7x faster inference while maintaining or improving task performance. The model uses self-supervised learning to estimate representation sufficiency rather than relying on predefined layer depths or heuristic rules.