3 papers
cs.CV2026
Magnitude-Direction Decoupling for Fast Video Generation with Flow Matching Models
Haonan Xu, Feiyang Chen, Songkui Chen +5
Flow matching models for video generation achieve impressive performance but suffer from high computational overhead due to iterative denoising. In fact, the original model is not…
cs.CV2026
Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini
Madhuri Shanbhogue, Zhe Li, Shanfeng Zhang +86
We introduce Gemini Embedding 2, a native multimodal embedding model that allows embedding video, audio, image, and text modalities in a unified representation space. We leverage t…
cs.CV2026
Cross-Resolution Distribution Matching for Diffusion Distillation
Feiyang Chen, Hongpeng Pan, Haonan Xu +3
Diffusion distillation is central to accelerating image and video generation, yet existing methods are fundamentally limited by the denoising process, where step reduction has larg…