sparsed-sparse-attention-diffusion-lm

Achieve up to 1.50x speedup in diffusion language models by computing head-specific sparse attention patterns once during early denoising steps and reusing them across all subsequent iterations, while preserving full attention in critical early phases to maintain generation quality and accuracy.

Independent GitHub snapshot · Automated classification · Original documentation governs