Kavli Affiliate: Feng Yuan
| First 5 Authors: Jingtao Ding, Yunke Zhang, Yu Shang, Yuheng Zhang, Zefang Zong
| Summary:
The concept of world models has garnered significant attention due to
advancements in multimodal large language models such as GPT-4 and video
generation models such as Sora, which are central to the pursuit of artificial
general intelligence. This survey offers a comprehensive review of the
literature on world models. Generally, world models are regarded as tools for
either understanding the present state of the world or predicting its future
dynamics. This review presents a systematic categorization of world models,
emphasizing two primary functions: (1) constructing internal representations to
understand the mechanisms of the world, and (2) predicting future states to
simulate and guide decision-making. Initially, we examine the current progress
in these two categories. We then explore the application of world models in key
domains, including autonomous driving, robotics, and social simulacra, with a
focus on how each domain utilizes these aspects. Finally, we outline key
challenges and provide insights into potential future research directions.
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