Author

Chaojun Ni

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#artificial intelligence Jul 2026

HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models

HALO-WA is proposed, a hybrid-attention latent-guided online reinforcement learning (RL) framework for WA models, which leverages latent features and action priors from the WA generation process through a lightweight actor-critic adapter to enable fast online adaptation to real deployment errors.

An-Gen Ye, Wei-Jie Ke, Xiao-Feng Wang et al. · arXiv.org · 1 citation

Jul 2026

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

GigaWorld-Policy-0.5 preserves the training benefits of future visual dynamics while improving inference efficiency for robot control, and introduces a Mixture-of-Transformers architecture that separates visual dynamics modeling and action generation into specialized experts.

GigaWorld Team, Angen Ye, Ang-Yuan Ma et al. · arXiv.org · 3 citations