SOURCE-LINKED INTELLIGENCE
rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference
Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured station keeps the jobs tractable for current policies. Vision-Language-Action (VLA) models now dominate as the policy paradigm for these robots. The inference latency of VLA models directly affects robot responsiveness and motion smoothness. However, existing VLA inference frameworks do not fully exploit the characteristics of embodied workloads or account for the distinct bottlenecks across different stages of VLA inference. In this paper, we first
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T17:34:43.000Z
- arXiv · Artificial Intelligence · 2026-09-16T17:34:43.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.