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A single adversarial token can bypass most safety filters.
Robotic recovery is now 74-93% faster by triggering corrections from action proposal disagreement and using efficient visual residuals, not slow VLM reasoning.
Integration of diverse robot policies can be streamlined from hours to minutes, revolutionizing how we deploy and evaluate robotic systems.
A surprisingly simple VLA model, StarVLA-$\alpha$, beats more complex systems on real-world robotics tasks, suggesting that VLM backbones are more critical than intricate architectures.