Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms
The rapid evolution of video generation has enabled models to simulate complex physical dynamics and long-horizon causalities, positioning them as potential world simulators. However, a critical gap still remains between the theoretical capacity for world simulation and the heavy computational costs of spatiotemporal modeling. To address this, we comprehensively and systematically review video generation frameworks and techniques that consider efficiency as a crucial requirement for practical world modeling. We introduce a novel taxonomy in three dimensions: efficient modeling paradigms, efficient network architectures, and efficient inference algorithms. We further show that bridging this efficiency gap directly empowers interactive applications such as autonomous driving, embodied AI, and game simulation. Finally, we identify emerging research frontiers in efficient video-based world modeling, arguing that efficiency is a fundamental prerequisite for evolving video generators into general-purpose, real-time, and robust world simulators.
69cbd4933f84a0971be6690b
Muyang He
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2026-04-01T08:35:49.310Z
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Isaache
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Isaachhe
69cbd4933f84a0971be6690c
Hanzhong Guo
69cbd4933f84a0971be6690d
Junxiong Lin
69cbd4933f84a0971be6690e
Yizhou Yu
Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms
The rapid evolution of video generation has enabled models to simulate complex physical dynamics and long-horizon causalities, positioning them as potential world simulators. However, a critical gap still remains between the theoretical capacity for world simulation and the heavy computational costs of spatiotemporal modeling. To address this, we comprehensively and systematically review video generation frameworks and techniques that consider efficiency as a crucial requirement for practical world modeling. We introduce a novel taxonomy in three dimensions: efficient modeling paradigms, efficient network architectures, and efficient inference algorithms. We further show that bridging this efficiency gap directly empowers interactive applications such as autonomous driving, embodied AI, and game simulation. Finally, we identify emerging research frontiers in efficient video-based world modeling, arguing that efficiency is a fundamental prerequisite for evolving video generators into general-purpose, real-time, and robust world simulators.
Video generation models capable of simulating complex physical dynamics and long-horizon causality require efficient frameworks to become practical world simulators for interactive applications.
video generation world simulators spatiotemporal modeling efficient modeling paradigms efficient network architectures efficient inference algorithms autonomous driving embodied AI game simulation