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About this paper
Yuanchun Guo, Bingyan Liu
Reflex, a streaming inference system, enables real-time, continuous control for Flow Matching Vision-Language-Action (VLA) models by re-architecting their serving loop, achieving a 2.58x inference speedup and reducing reaction latency by up to 54% for stable 50Hz operation.
Key insights
- The timestep-invariance of VLA perception encoders allows for semantic partitioning of attention context, enabling efficient caching even with global timestep injection.
- Achieving long-horizon numerical stability in mixed-precision requires dynamic, precision-aware normalization to mitigate high-variance noise and prevent model collapse.
- Decoupling vision and policy streams asynchronously, coupled with future-state prediction, effectively hides vision latency and ensures accurate state-conditioned action generation for continuous control.
Summary by alphaXiv.
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