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cs.CV2026

Building Pretraining Data for World Models: An Unreal Engine-Based Pipeline for Action-Conditioned Video Generation

Haoyu Wang, Songchun Zhang, Haoran Li +3

Action-conditioned video models require large-scale visual data paired with control signals that are temporally aligned with the resulting scene transitions. Such supervision is di…

cs.CV2026

Long-Horizon Audio-Visual Generation for Persistent Stories and Interactive Worlds

Nan Duan, Haoyang Huang, Weiyang Jin +13

Video generation is progressing beyond isolated clips toward long-form narratives and interactive worlds, requiring models to preserve identities, follow user controls, and remain…

cs.CV2026

EchoWM: Open and Enterable Omnimodal World Models

Songchun Zhang, Yaowei Li, Junhao Zhuang +19

We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, environmental sound, music an…

cs.CV2026

Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions

Luxury, Jie Huang, Zihao Fan +25

While recent autoregressive video diffusion models achieve remarkable streaming quality, they remain confined to low resolutions (e.g., 480P), leaving efficient, scalable, real-tim…

cs.CV2026

Echo-Memory: A Controlled Study of Memory in Action World Models

Wayne King, Zeyue Xue, Yuxuan Bian +13

We present \textbf{Echo-Memory}, a controlled study of memory mechanisms in action-conditioned world models. These models generate multi-segment videos from a first frame, text pro…