AI · Studies · 2026-10-29 14:10
The paper identifies that Diffusion Transformers (DiTs) suffer from exploding token counts and structural distortion when generating images beyond their training resolution, since full attention becomes prohibitively expensive. It proposes adaptive receptive-field attention to mitigate these issues efficiently.
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