Tutorial Maps World Models to Robot Actions; Clarifies Embodied AI Framework新教程连接世界模型与机器人行动，澄清具身智能设计空间
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Xiaoxiong Zhang et al. released an arXiv tutorial paper on July 1, 2026, presenting a design-space view of world models and introducing "world action models" that connect predicted future states with executable robot actions.
The paper categorizes existing methods into observation-space and state-space world models, comparing their trade-offs across visual fidelity, spatial structure, physical interpretability, and control usability.
Four representative world-action paradigms are summarized: imagine-then-execute, video-feature-conditioned action prediction, joint video-action modeling, and auxiliary video prediction for policy learning.