1 citations · 2 across the 14 of their papers we have counts for
14 papers · 1 filter
Cross-Space Distillation: Teaching One-Step Students with Modern Diffusion Teachers
Anh Nguyen, Ngan Nguyen, Duc Vu +11
Modern one-step diffusion models achieve impressive quality through distribution-based timestep distillation. Yet, they rely on a critical assumption: Teacher and Student must inha…
Can Cross-Layer Transcoders Replace Vision Transformer Activations? An Interpretable Perspective on Vision
Gerasimos Chatzoudis, Konstantinos D. Polyzos, Zhuowei Li +4
Understanding the internal activations of Vision Transformers (ViTs) is critical for building interpretable and trustworthy models. While Sparse Autoencoders (SAEs) have been used…
MPDiT: Multi-Patch Global-to-Local Transformer Architecture For Efficient Flow Matching and Diffusion Model
Quan Dao, Dimitris Metaxas
Transformer architectures, particularly Diffusion Transformers (DiTs), have become widely used in diffusion and flow-matching models due to their strong performance compared to con…
Overcoming the Curvature Bottleneck in MeanFlow
Xinxi Zhang, Shiwei Tan, Quang Nguyen +7
MeanFlow offers a promising framework for one-step generative modeling by directly learning a mean-velocity field, bypassing expensive numerical integration. However, we find that…
AutoEdit: Automatic Hyperparameter Tuning for Image Editing
Chau Pham, Quan Dao, Mahesh Bhosale +3
Recent advances in diffusion models have revolutionized text-guided image editing, yet existing editing methods face critical challenges in hyperparameter identification. To get th…
Discrete Noise Inversion for Next-scale Autoregressive Text-based Image Editing
Quan Dao, Xiaoxiao He, Ligong Han +6
Visual autoregressive models (VAR) have recently emerged as a promising class of generative models, achieving performance comparable to diffusion models in text-to-image generation…