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VC-Attention is proposed, a training-free low-bit attention framework that addresses diffusion Transformers and quantization scale by pairing Value smoothing with a fused probability Cast, and improves fidelity over low-bit baselines.
K-means, previously relegated to offline processing, gets a 17.9x speed boost on modern GPUs thanks to Flash-KMeans' clever IO and contention optimizations.
