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
To the knowledge, this work provides the first demonstration of real-time cross-terrain whole-body teleoperation on a humanoid robot, alongside object interaction, stable responses to missing supports, and robust recovery from falls.
Zi-Yang Cheng, Tian-Shu Tang, Jin-Xi Lan et al.· 0 citations
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
These findings establish that static analysis alone is insufficient for skill security, motivating defense-in-depth architectures that combine fast static pre-screening with semantic review.
Xinze Chen, Chi Zhang, Ping Ji et al.· 0 citations
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
A deterministic routing stress test over 20,000 skills shows the functional impact: skills with valid routing metadata are retrieved more reliably from startup descriptions than skills with routing defects, while AI-marked skills show more safety and portability problems.
Chi Zhang, Yimin Liu, Xinze Chen et al.· 0 citations
GigaBrain-WBC-0.5, the first Behavior World Model for humanoid whole-body control, is presented, which trains a causal Transformer to jointly predict its next action, next state, and the distribution over its next latent behavior command, so the network that acts also models how the environment shapes what it can do ne...
Zi-Yang Cheng, Tian-Shu Tang, Jin-Xi Lan et al.· 1 citation
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