Summary
Reflex introduces streaming inference for vision-language-action models, enabling real-time robot control at much higher control frequencies than standard VLA generation pipelines. By reformulating VLA generation as an incremental streaming process rather than a full-sequence generation step, Reflex decouples inference latency from action-chunk length and allows the robot to begin executing the earliest tokens of an action sequence before generation is complete.
Key Contributions
- Streaming inference formulation: VLA outputs are consumed incrementally as they are generated, eliminating the full-sequence generation bottleneck
- Enables real-time VLA control frequencies compatible with high-speed manipulation tasks
- Accepted at ICML 2026, providing strong peer-reviewed validation of the approach
- Addresses the fundamental latency-capability tradeoff in deploying large VLA models for reactive robot control
Significance
ICML 2026 acceptance for a core VLA inference efficiency paper signals mainstream recognition of the real-time deployment gap — Reflex offers a principled streaming solution that does not sacrifice model capability for speed, potentially enabling a new class of reactive foundation-model-based robot controllers.