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cs.LG2026
RT-Lynx: Putting GEMM Sparsity in the Right Place for Diffusion Models
Xing Cong, Hanlin Tang, Kan Liu +3
Diffusion Transformers (DiT) achieve strong performance in image generation but incur substantial inference costs. While prior work has reduced this cost via quantization and disti…
cs.LG2026
Shiva-DiT: Residual-Based Differentiable Top- Selection for Efficient Diffusion Transformers
Jiaji Zhang, Hailiang Zhao, Jiaju Wu +3
Diffusion Transformers (DiTs) are costly at high resolution because self-attention scales quadratically with token sequence length. Existing pruning methods do not jointly provide…