vAttention: Verified Sparse Attention 事件
PRODUCT_LAUNCH2026-05-26影响: MEDIUM
vAttention: Verified Sparse Attention arXiv:2510.05688v2 Announce Type: replace-cross Abstract: State-of-the-art sparse attention methods for reducing decoding latency fall into two main categories: approximate top-$k$ (and its extension, top-$p$) and recently introduced sampling-based estimation. However, these approaches are fundamentally limited in their ability to approximate full attention: they fail to provide consistent approximations across heads and query vectors and, most critically,
相关产品查看全部 (10)
相关报道查看全部 (1)
vAttention: Verified Sparse Attention
ArXiv CS.AI2026-05-26