8 papers
RIGen: Beyond Action Following with Reciprocal Interaction in Generative Gameplay
Mengfei Li, Yi Zhang, Xingtong Ge +8
Generative gameplay requires more than immediate responses to player actions.Actions should have persistent consequences, while the generated world should act according to its own…
Salt++: Context-Aligned Post-Training for Few-Step Streaming Multimodal Generation
Xingtong Ge, Yutong Wang, Lunjie Zhu +7
Few-step streaming audio--video generation requires both causal modeling and step distillation, yet standard training recipes face two context-related challenges. Teacher forcing p…
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…
Neighbor GRPO: Contrastive ODE Policy Optimization Aligns Flow Models
Dailan He, Guanlin Feng, Xingtong Ge +6
Group Relative Policy Optimization (GRPO) has shown promise in aligning image and video generative models with human preferences. However, applying it to modern flow matching model…
Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting
Xingzhong Hou, Jie Wu, Boxiao Liu +5
Image inpainting is the task of reconstructing missing or damaged parts of an image in a way that seamlessly blends with the surrounding content. With the advent of advanced genera…
ADT: Tuning Diffusion Models with Adversarial Supervision
Dazhong Shen, Guanglu Song, Yi Zhang +5
Diffusion models have achieved outstanding image generation by reversing a forward noising process to approximate true data distributions. During training, these models predict dif…
See Further When Clear: Curriculum Consistency Model
Yunpeng Liu, Boxiao Liu, Yi Zhang +4
Significant advances have been made in the sampling efficiency of diffusion models and flow matching models, driven by Consistency Distillation (CD), which trains a student model t…