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HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models
World-action (WA) models can generate long-horizon action chunks for general-purpose robotic manipulation, but they remain vulnerable to calibration, perception, and contact-dynamics errors in real-world precision tasks, often failing in the final few millimeters of alignment or insertion. We propos
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