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...
The Band-Attention Modulation Network (BAM-Net) is proposed, a novel framework that pioneers learnable, fine-grained modulation of frequency components for forgery detection and exhibits exceptional generalization in cross-dataset, cross-compression, and cross-manipulation scenarios.
Zhi-Da Zhang, Wen-Kui Yang, Xin Ma et al.· 1 citation
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
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