Article

Let It Be Simple: Research on One-Step Action Generation for Vision-Language-Action Models

The paper finds that VLA action generation differs from text-to-image generation: merely biasing the training timestep distribution toward the noise endpoint yields strong one-step policies on LIBERO, LIBERO-Plus, LIBERO-Pro, and real-world robot tasks. For open-source VLA models with different architectures, directly replacing iterative decoding with a single forward pass often performs comparably to the original multi-step decoding on LIBERO, CALVIN, and SimplerEnv.

Part of the event: VLA single-step action generation: biasing toward the noise-end timestep yields a strong policy

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