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AlayaVista is presented, a camera-controllable streaming video world model that decouples panoramic world evolution from perspective observation synthesis, and MUGEN, a large-scale real-world panoramic video dataset containing 1,318 hours of videos at resolutions of at least 4K, together with rich semantic and geometric annotations.
Digital twins no longer need to be passive mirrors: structuring perception, memory, and task execution into a self-evolving closed loop enables cyber-physical systems to autonomously learn and optimize from operational feedback.
AlayaWorld achieves unprecedented long-horizon video generation with just four sampling steps, revolutionizing how we create interactive virtual environments.
Surprise Forcing redefines resource allocation in video generation, leading to improved visual quality and consistency without sacrificing streaming speed.
Interactive game worlds can now leverage a scalable data engine that captures 90 hours of gameplay, setting a new standard for state-aware modeling.
