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PearlVLA: Progressive Embodied Action-Plan Refinement in Latent Space
Current Vision-Language-Action (VLA) models face a trade-off between efficient action generation and explicit deliberation. Directly decoding actions from vision-language backbone representations enables low-latency control, whereas textual reasoning, pixel-level subgoals, or world-model evaluation
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