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Sep 2026
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.
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Preprint
Aug 2026
Frozen vision-language-action (VLA) policies generate temporally extended action chunks, but long-horizon manipulation remains vulnerable to accumulated execution error and visual aliasing across task stages. Successful rollouts provide useful corrective evidence, yet current frame retrieval can return progress-misalig...
Yuze Fan, Yue Cao, Peng-Jie Gao et al.
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Preprint
Aug 2026
Predictive video models have emerged as promising world models by learning latent visual dynamics from large-scale video. Yet these models remain challenged by physical events under occlusion, where later predictions may depend on object evidence that is no longer available in the current view. Addressing this challeng...
Yuanruyi, Yue Cao, Haojia Gao et al.
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