25 papers
RefVideo-6M: A Reliable Reference-Based Dataset for Instructional Video Editing
Bojia Zi, Xiaoyan Yang, Yu Zhou +7
Recent advances in video editing have been largely driven by large-scale instruction-based datasets. However, existing datasets still suffer from two critical limitations. First, t…
Sample-Adaptive Latent Rewards for Uncertainty-Guided Diffusion Post-Training
Rui Li, Yuanzhi Liang, Ke Hao +4
Latent reward models can supervise visual diffusion models without decoding intermediate states into pixel space. This makes alignment with human preferences more efficient. Howeve…
CineWeaver: Training-Free Reference-Controllable Multi-Shot Long Video Generation for Cinematic Storytelling
Yuyang Huang, Yabo Chen, Wenrui Dai +6
Cinematic video generation is challenging for text-to-video diffusion models due to concurrent requirements on multi-shot generation, fine-grained controllability over characters a…
MMOE: Modernizing Diffusion Transformers with Efficient Expert Design
Yanhao Jia, Jiepeng Wang, Haibin Huang +3
Modern large language models scale successfully by pairing capacity growth with efficiency, keeping per-token and deployment costs under control as capacity grows. AIGC Foundation…
ShotPlan: Cinematic Video Generation with Learnable Planning Token
Su Guo, Guangce Liu, Haosen Yang +7
Current video generation models achieve impressive results in single-shot generation, yet remain limited in cinematic video generation, where coherent narratives and effective mult…
Generative Transmission: Rethinking Computation, Bandwidth, and Memory in Communication
Xiangyu Chen, Jixiang Luo, Yuankai Fan +3
Under the AI Flow framework, communication is shifting from transmitting fidelity-oriented information flows toward delivering task-oriented and perception-oriented token flows acr…