Latent diffusion models enable high-quality video generation, but video VAE encoding and decoding remain computationally expensive. Existing methods use stage-specific lightweight operators, yet either constrain spatial and temporal computation jointly or remove temporal computation altogether, without distinguishing t...
Shi-Qiao Gu, Yang Yong, Feng-Jun Zhong et al.· 0 citations
World Action Models (WAMs) incorporate visual representations from video generation backbones to guide action prediction. Recent efficient WAMs adopt Mixture-of-Transformers (MoT) architectures and compute video representations once for reuse by the action expert. However, intra-expert iteration (\ie, multi-step action...
Cheng-Tao Lv, Jin-Yang Du, Shu-Yi Feng et al.· 0 citations
Native unified modelling is position as a promising path towards systems that perceive, reason and create within a fully end-to-end framework through SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free and VAE-free architecture.
Hai-Wen Diao, Jia-Hao Wang, Chen-Jing Ding et al.· 3 citations
The proposed MaskFlow, a training framework for precise localization, consistent background preservation, and seamless boundary transitions, incorporates the mask into the probability path and flow-matching objective, coordinating generation within the editable region with source preservation outside it.
Rui Xu, Yang Yong, Shun-Zi Yang et al.· 0 citations
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