Rank-Factorized Implicit Neural Bias: Scaling Super-Resolution Transformer with FlashAttention 事件

Rank-Factorized Implicit Neural Bias: Scaling Super-Resolution Transformer with FlashAttention arXiv:2603.06738v2 Announce Type: replace-cross Abstract: Recent Super-Resolution~(SR) methods mainly adopt Transformers for their strong long-range modeling capability and exceptional representational capacity. However, most SR Transformers rely heavily on relative positional bias~(RPB), which prevents them from leveraging hardware-efficient attention kernels such as FlashAttention. This limitation i