Author

Bingning Wang

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#natural language process... May 2026

UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification

UniPrefill is proposed, a prefill acceleration framework applicable to virtually any model architecture, which directly accelerates the model's computation at the token level and achieves up to 2.1x speedup in Time-To-First-Token (TTFT), with the acceleration becoming increasingly pronounced as the number of concurrent...

Qihang Fan, Huai-Bo Huang, Zhiying Wu et al. · arXiv.org · 2 citations

Preprint Aug 2026

FlashPrefill V2: Block-Sparse Prefill Attention for Long-Context LLM Serving

This paper introduces a mean correction term that effectively suppresses the approximation error, keeping performance degradation manageable even at extreme sparsity levels, and redesigns the sparse attention operator with PackGQA memory access, warp specialization, and pingpong pipelining.

Qihang Fan, Huai-Bo Huang, Zhiying Wu et al. · 2 citations