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RefAdapt-DiT: Adaptive Joint Attention for Reference-Conditioned Diffusion Transformers
Diffusion Transformers (DiTs) have become the standard backbone for high-quality generative modeling, yet deploying them in conditional generation tasks remains computationally prohibitive because bidirectional joint attention repeatedly processes large reference streams. While existing optimization
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