Author

Yu-Han Xie

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Preprint Oct 2026

What Limits Cross-Task Generalization in World Action Models?

Cross-task generalization remains difficult for world action models (WAMs), even when their predicted futures depict plausible manipulation. This gap can be attributed directly: we make this gap directly testable by decoupling a WAM into a world model and an inverse-dynamics model (IDM), then holding the IDM fixed whil...

Chen Zhao, Zi-Peng Ye, Yi-Han Lin et al. · 0 citations

Preprint Aug 2026

Beyond Placement and Articulation: Usage-Driven Code Scenes for Embodied Interaction

RoomWright is presented, an agentic usage-driven framework for generating 3D scenes represented entirely as code for embodied interaction, providing interactive environments for embodied AI and policy learning.

Zijian Xiao, Zi-Peng Ye, Jin-Kun Hao et al. · 1 citation

#machine learning Preprint Jul 2026

EvoCUA-1.5: Online Reinforcement Learning for Multi-turn Computer-Use Agents

EvoCUA-1.5 extends self-evolving computer-use agents from offline experience learning to online reinforcement learning, where policies interact with executable sandbox environments and improve from verifiable task outcomes and provides a practical framework for scaling online RL in multi-turn computer-use agents.

Mianqiu Huang, Taofeng Xue, Chong Peng et al. · 1 citation