Author

Shuoshuo Xue

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Preprint Sep 2026

EWAM: Emergent Depth-Wise Specialization in a Unified Embodied Model -- From Semantic Understanding through Visual Foresight to Action

Vision-language-action (VLA) policies emphasize semantic understanding, whereas world-action models (WAMs) learn predictive representations of environment dynamics. Systems that expose a policy to both sources often still concentrate action computation on a single expert. We present EWAM, an action-centric unified embo...

Hao Wang, Jia-Jun Wen, Jing-Zhi Liu et al. · 0 citations

Jul 2026

PAVXploreRL: Physical-Action-Visual World Model Reinforcement Learning with Action Exploration

PAVXploreRL is a reinforcement learning framework built on a pretrained latent world model that explicitly optimizes PAV objectives through reward-driven training, and jointly leverages ID trajectories and noise-driven OOD action exploration, without paired video supervision.

Hanyin Wang, Zijun Wang, Shuoshuo Xue et al. · arXiv.org · 0 citations