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cs.CV2026
QK-Edit: Revisiting Attention-based Injection in MM-DiT for Image and Video Editing
Tiancheng Shen, Zilong Huang, Xiangtai Li +6
Multimodal Diffusion Transformers (MM-DiTs) have recently emerged as a powerful framework for unified text-vision synthesis, surpassing traditional U-Net architectures in generativ…
cs.CV2026
DreamSR: Towards Ultra-High-Resolution Image Super-Resolution via a Receptive-Field Enhanced Diffusion Transformer
Qingji Dong, Hang Dong, Mingqin Chen +2
Large-scale pre-trained diffusion models have been extensively adopted for real-world image Super-Resolution because of their powerful generative priors through textual guidance. H…
cs.CV2026
NextFlow: Unified Sequential Modeling Activates Multimodal Understanding and Generation
Huichao Zhang, Liao Qu, Yiheng Liu +33
We present NextFlow, a unified decoder-only autoregressive transformer trained on 6 trillion interleaved text-image discrete tokens. By leveraging a unified vision representation w…