Author

Wei-Jie Ke

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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

Preprint Aug 2026

GigaBrain-0.7: Scaling Embodied Foundation Models to Emergent Capabilities with a Three-System Architecture

This work presents GigaBrain-0.7, an embodied foundation model with substantially improved generalization across diverse robot embodiments, and introduces one-stage alignment training that jointly optimizes vision-language understanding and multi-embodiment action generation.

GigaBrain Team, An-Gen Ye, Axiang Sun et al. · 7 citations · ⚡1