Unverified50% confidenceBenchmarkExact time
当行数n约2000、m取64时,ISAB相比标准注意力显存节省可达30倍
1
Sources
50%
Confidence
Long-term
Relevance
7/19/2026
First Seen
Sources
变长矩阵分类:如何为无序集合数据选择神经网络架构
Related Claims
Unverified128K长度的序列所需的注意力计算量是4K长度序列的1024倍64% similarUnverifiedAt a sequence length of 4096, the N×N attention matrix alone consumes approximately 64 MB of memory in FP16 precision.63% similarUnverifiedThe security strength of 256-bit ECC is approximately equivalent to that of 3072-bit RSA.62% similarUnverifiedOn a 128GB MacBook Pro M3 Max, independent benchmarks show DS4 achieving a generation speed of 26.68 tokens per second.60% similarUnverified128K上下文窗口的注意力矩阵规模是32K窗口的16倍60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/558151API
curl https://kongchang.com/api/v1/knowledge/claims/558151MCP
get_claim(id=558151)