arXiv 2610.17227 · cs.CV · 2026-10-12
AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers
Javad Rajabi, Koorosh Roohi, David B. Lindell, Babak Taati
University of Toronto Computer Science
In latest · #217 Added on 2026-10-21
One-line takeaway
AReA adapts the attention receptive field across denoising steps so diffusion transformers generate beyond-training resolutions more cheaply.
AReA 让扩散 Transformer 的注意力感受野随去噪步骤自适应收窄，更省算力地生成超高分辨率图像。
Read on arXiv PDF Hugging Face discussion Code Project page
Topics & disciplines
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About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.