collaborators

9 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.MM2026

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…

cs.CV2025

Video-As-Prompt: Unified Semantic Control for Video Generation

Yuxuan Bian, Xin Chen, Zenan Li +4

Unified, generalizable semantic control in video generation remains a critical open challenge. Existing methods either introduce artifacts by enforcing inappropriate pixel-wise pri…

cs.CV2025

OmniMotion-X: Versatile Multimodal Whole-Body Motion Generation

Guowei Xu, Yuxuan Bian, Ailing Zeng +6

This paper introduces OmniMotion-X, a versatile multimodal framework for whole-body human motion generation, leveraging an autoregressive diffusion transformer in a unified sequenc…