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cs.CL2026
FlashPrefill V2: Block-Sparse Prefill Attention for Long-Context LLM Serving
Qihang Fan, Huaibo Huang, Zhiying Wu +2
Long-context modeling is a pivotal capability for Large Language Models, yet the quadratic complexity of attention remains a critical bottleneck, particularly during the compute-in…
cs.CL2026
UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification
Qihang Fan, Huaibo Huang, Zhiying Wu +2
As large language models (LLMs) continue to advance rapidly, they are becoming increasingly capable while simultaneously demanding ever-longer context lengths. To improve the infer…
cs.CL2026
FlashPrefill: Instantaneous Pattern Discovery and Thresholding for Ultra-Fast Long-Context Prefilling
Qihang Fan, Huaibo Huang, Zhiying Wu +3
Long-context modeling is a pivotal capability for Large Language Models, yet the quadratic complexity of attention remains a critical bottleneck, particularly during the compute-in…