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cs.CV2026

Masked Visual Actions for Unified World Modeling

Hadi Alzayer, Wenlong Huang, Haonan Chen +8

Video models absorb rich priors over how the visual world moves, interacts, and responds to contact, making them promising substrates for robotic world modeling. The central challe…

cs.CV2026

TinyHistory: Lightweight Video History Embeddings via Two-Stage Context Learning

Lvmin Zhang, Shengqu Cai, Muyang Li +6

History context is central to autoregressive video generation, driving consistency and storytelling for both commercial models and personal use cases. For example, personal users,…

cs.CV2026

Spectral Progressive Diffusion for Efficient Image and Video Generation

Howard Xiao, Brian Chao, Lior Yariv +1

Diffusion models have been shown to implicitly generate visual content autoregressively in the frequency domain, where low-frequency components are generated earlier in the denoisi…

cs.CV2026

GeoFlow: Enforcing Implicit Geometric Consistency in Video Generation

Jan Ackermann, Shengqu Cai, Boyang Deng +3

Generating geometrically consistent videos remains an open challenge: text-to-video diffusion models trained on web-scale data treat geometry only implicitly, leading to object def…

cs.CV2026

Mode Seeking meets Mean Seeking for Fast Long Video Generation

Shengqu Cai, Weili Nie, Chao Liu +8

Scaling video generation from seconds to minutes faces a critical bottleneck: while short-video data is abundant and high-fidelity, coherent long-form data is scarce and limited to…

cs.CV2026

VULCAN: Tool-Augmented Multi Agents for Iterative 3D Object Arrangement

Zhengfei Kuang, Rui Lin, Long Zhao +3

Despite the remarkable progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, their application to complex 3D scene manipulation remains underexplored. I…