3 papers
cs.CV2026
Histogram-constrained Image Generation
Haoming Liu, Yuanhe Guo, Yijia Cao +2
Diffusion models have emerged as a dominant paradigm in generative modeling, enabling high-fidelity sampling from complex data distributions. Despite impressive capabilities, contr…
cs.LG2025
From Navigation to Refinement: Revealing the Two-Stage Nature of Flow-based Diffusion Models through Oracle Velocity
Haoming Liu, Jinnuo Liu, Yanhao Li +5
Flow-based diffusion models have emerged as a leading paradigm for training generative models across images and videos. However, their memorization-generalization behavior remains…
cs.AI2025
HilbertA: Hilbert Attention for Image Generation with Diffusion Models
Shaoyi Zheng, Wenbo Lu, Yuxuan Xia +2
Designing sparse attention for diffusion transformers requires reconciling two-dimensional spatial locality with GPU efficiency, a trade-off that current methods struggle to achiev…