108 citations · 313 across the 50 of their papers we have counts for
5 papers · 1 filter
Enhancing Autoregressive Video Generation via Representation Adversarial Distillation
Fangyu Lin, Xingtong Ge, Lunjie Zhu +8
Few-step autoregressive video generation enables efficient streaming synthesis, but errors introduced in early temporal blocks are reused as context and can propagate through subse…
Omni-LiveAvatar: Minute-Level Real-Time Streaming Joint Audio-Video Avatar Generation
Lunjie Zhu, Xingtong Ge, Fangyu Lin +7
Joint audio-video generative models serve as foundation for immersive and interactive digital-human generation. Nevertheless, most existing models rely on bidirectional attention a…
Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation
Xingtong Ge, Yi Zhang, Yushi Huang +6
Distilling video generation models to extremely low inference budgets (e.g., 2--4 NFEs) is crucial for real-time deployment, yet remains challenging. Trajectory-style consistency d…
Improving Joint Audio-Video Generation with Cross-Modal Context Learning
Bingqi Ma, Linlong Lang, Ming Zhang +5
The dual-stream transformer architecture-based joint audio-video generation method has become the dominant paradigm in current research. By incorporating pre-trained video diffusio…
AR-CoPO: Align Autoregressive Video Generation with Contrastive Policy Optimization
Dailan He, Guanlin Feng, Xingtong Ge +5
Streaming autoregressive (AR) video generators combined with few-step distillation achieve low-latency, high-quality synthesis, yet remain difficult to align via reinforcement lear…