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AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers
Generating images beyond the training resolution of Diffusion Transformers (DiTs) remains challenging, as the number of tokens grows rapidly with resolution, full attention becomes expensive, and outputs often suffer from structural distortions and degraded detail. We identify uniform full attention
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