DeepJEPA: Scaling World Models from Within
World-model planners typically scale outward by rolling farther, sampling more trajectories, or optimizing longer, while assigning the same computation to every imagined transition. We show that making every transition uniformly deeper wastes computation and can degrade planning because useful refinement is concentrate...
Zi-Jian Jin, Yun-Bei Zhang, Yuan-Zhe Liu et al.
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