Video diffusion models are increasingly developed into specialized models for diverse downstream tasks, and this development often includes a distillation stage, for example to accelerate sampling or to improve long-video generation. This stage is typically repeated for every specialized model. We introduce LongLive-Pl...
Shuai Yang, Luo-Zhou Wang, Wei Huang et al.· 0 citations
Advances in generative models have improved video fidelity, enabling long-horizon generation, interactive world modeling, and evolving visual environments. Autoregressive (AR) video generation extends visual sequences through causal rollouts. However, a fundamental bottleneck emerges: as the generated sequence expands,...
Harold Haodong Chen, Rong-Jin Guo, Di-Sen Lan et al.· 0 citations
SolarWM, a fully open foundation for building interactive video world models from data preparation through long-horizon inference, is introduced, providing a reproducible and extensible foundation for interactive world-model research.
Jun-Chao Huang, Guian Fang, Sheng-Ju Qian et al.· 6 citations
The method combines chunk-wise autoregressive adaptation, Source-Anchored Distribution Matching Distillation, and Long-Horizon Autoregressive Distillation to reduce train--inference mismatch, preserve source fidelity during two-step generation, and mitigate accumulated temporal drift.
Yi-Cheng Xiao, Wenxun Dai, Xinran Qin et al.· 5 citations
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