19 papers
Self Gradient Forcing: Native Long Video Extrapolation
Junhao Zhuang, Shiyi Zhang, Yuxuan Bian +11
Recent autoregressive video diffusion methods are increasingly built upon Self Forcing, where the student is trained on histories produced by its own rollout rather than ground-tru…
Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization
Xiaoxuan He, Siming Fu, Zeyue Xue +9
Group Relative Policy Optimization has emerged as essential for aligning video diffusion models with human preferences, but faces a critical computational bottleneck: training a 14…
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…
HPSv3++: Scaling Reward Models Across the Full Spectrum of Diffusion Model Capabilities
Yijun Liu, Jie Huang, Zeyue Xue +5
Reward models guide text-to-image (T2I) systems toward outputs aligned with human preferences. However, typical reward models such as HPSv3 are trained on pre-annotated data from e…
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…
Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation
Yuxuan Bian, Zeyue Xue, Songchun Zhang +9
We present Echo Infinity, an autoregressive (AR) framework towards real-time infinite video generation that employs a learnable evolving memory to dynamically filter, abstract, and…