Unverified50% confidenceFactExact time
Linformer 将注意力矩阵低秩近似为 O(n) 复杂度，FlashAttention 通过重排计算顺序降低 GPU 内存带宽占用，Longformer 引入滑动窗口注意力
1
Sources
50%
Confidence
Long-term
Relevance
7/13/2026
First Seen
Sources
Related Claims
UnverifiedLongformer由Allen AI提出，采用滑动窗口局部注意力加全局注意力token的组合策略，将复杂度从O(n²)降至O(n)79% similarUnverifiedOptimization techniques such as Flash Attention and sparse attention can compress memory complexity to near-linear.79% similarUnverifiedThe computational complexity of standard self-attention is quadratic with respect to sequence length, and achieving a context of one million tokens requires introducing techniques such as sparse attention, sliding window attention, and KV Cache compression.78% similarVerifiedFlash Attention significantly reduces GPU memory usage and raises the physically available window limit through IO-aware block computation.77% similarVerifiedFlashAttention reduces GPU memory usage from being proportional to the square of the sequence length to a linear relationship by redesigning the memory access pattern of the attention computation.77% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/497085API
curl https://kongchang.com/api/v1/knowledge/claims/497085MCP
get_claim(id=497085)