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cs.CV2026
Sink-Sparse Hybrid Attention for Efficient Inference in T2I/T2V Diffusion Transformers
Bingxin Xing, Yu Zhang, Jiatong Ding +2
Diffusion Transformers (DiTs) have become a common backbone for high-quality text-to-image and text-to-video generation, but repeated dense self-attention remains a major inference…
cs.CV2025
ARFlow: Autoregressive Flow with Hybrid Linear Attention
Mude Hui, Rui-Jie Zhu, Songlin Yang +5
Flow models are effective at progressively generating realistic images, but they generally struggle to capture long-range dependencies during the generation process as they compres…