From Masks to Worlds: A Hitchhiker's Guide to World Models
This is not a typical survey of world models; it is a guide for those who
want to build worlds. We do not aim to catalog every paper that has ever
mentioned a ``world model". Instead, we follow one clear road: from early
masked models that unified representation learning across modalities, to
unified architectures that share a single paradigm, then to interactive
generative models that close the action-perception loop, and finally to
memory-augmented systems that sustain consistent worlds over time. We bypass
loosely related branches to focus on the core: the generative heart, the
interactive loop, and the memory system. We show that this is the most
promising path towards true world models.
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Jinbin Bai
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2025-10-24T16:01:08.585Z
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Jinbin Bai
BryanW
user
BryanW
68fb1095f158a71c5a2f58de
Yu Lei
68fb1095f158a71c5a2f58df
Hecong Wu
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Yuchen Zhu
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Shufan Li
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Yi Xin
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Xiangtai Li
claimed_verified
2025-12-15T08:14:47.763Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/U1g5H071pWRswGAG9UTpo.png
Xiangtai Li
LXT
user
LXT
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Molei Tao
68fb1095f158a71c5a2f58e5
Aditya Grover
68fb1095f158a71c5a2f58e6
Ming-Hsuan Yang
From Masks to Worlds: A Hitchhiker's Guide to World Models
This is not a typical survey of world models; it is a guide for those who
want to build worlds. We do not aim to catalog every paper that has ever
mentioned a ``world model". Instead, we follow one clear road: from early
masked models that unified representation learning across modalities, to
unified architectures that share a single paradigm, then to interactive
generative models that close the action-perception loop, and finally to
memory-augmented systems that sustain consistent worlds over time. We bypass
loosely related branches to focus on the core: the generative heart, the
interactive loop, and the memory system. We show that this is the most
promising path towards true world models.
The guide outlines a progression from early masked models to memory-augmented systems, emphasizing generative capabilities, interactive loops, and memory for building world models.
masked models representation learning unified architectures interactive generative models action-perception loop memory-augmented systems world models