Verified75% confidenceFactExact time
SSM is a class of architectures that process sequences in a linear recurrent manner, with representatives such as Mamba and Mamba-2.
3
Sources
75%
Confidence
Long-term
Relevance
10/12/2026
First Seen
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VerifiedMamba 等基于状态空间模型（SSM）的架构以线性复杂度实现序列建模，更适合实时推理79% similarUnverifiedSelective scan is the core operation of the Mamba family of SSMs, and its discretization parameter Δ, input matrix B and output matrix C all change dynamically with each token.79% similarUnverifiedMamba's key innovation is making the SSM's B and C matrices and the step size Δ functions of the input, thereby gaining content-aware gating capability while retaining linear complexity.76% similarUnverifiedThe SSD (State Space Duality) framework proposed by Mamba-2 reveals that SSMs with a specific structure are mathematically equivalent to a masked form of linear attention, allowing training to be parallelized using matrix multiplication.72% similarVerifiedState space models (SSMs) such as Mamba abandon the attention mechanism and use recurrent structures to achieve linear time complexity sequence modeling.72% similar
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