Verified65% confidenceTradeoffExact time
SSMs have a linear time complexity advantage in processing long sequences, whereas the attention computation complexity of standard Transformers is quadratic with respect to sequence length.
3
Sources
65%
Confidence
Long-term
Relevance
7/18/2026
First Seen
Sources
Related Claims
UnverifiedUnlike the global attention mechanism of Transformers, Mamba's computational complexity is linear with respect to sequence length.79% similarUnverifiedSSMs can reduce computational complexity for processing long sequences to linear level (O(n)).77% similarVerifiedTransformer架构的自注意力机制在处理长序列时面临二次方复杂度的计算开销，上下文长度翻倍则计算量增长四倍75% similarUnverified标准Transformer在处理需要精确计数、栈操作或复杂状态依赖的任务时表现不稳定，与其注意力机制的软寻址特性有关72% similarUnverified标准的Myers差分算法在处理数千行变更时时间复杂度会显著上升72% similar
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