arxivcs.ROcs.AI2026-07-05
HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models
Angen Ye, Weijie Ke, Xiaofeng Wang, Xinze Chen, Chaojun Ni, Guosheng Zhao, et al.
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…