Unverified50% confidenceFactExact time
Typical representatives of state space models include S4, Mamba and others, which write the recurrence as a continuous differential equation or discrete linear recurrence and achieve efficient parallel training with the help of convolution or selective scan.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/12/2026
First Seen
Valid until: 1/10/2027
Sources
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Related Claims
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71% similarUnverifiedLand surface forecasting systems based on Mamba-series structured state space models absorb non-stationary confounding events into the state transition matrix, leading to persistent prediction bias.70% similarUnverified2021年Albert Gu等人提出S4（Structured State Spaces for Sequence Modeling），通过HiPPO初始化和高效对角化计算使经典框架能处理长达数万步的序列依赖69% similarVerifiedState space models represented by Mamba compress historical information by maintaining a fixed-size hidden state, with both time and space complexity of O(1) during inference.68% similarUnverifiedFormal models can systematically enumerate the input space, identifying which state combinations are undefined in the requirements, thereby achieving completeness checking.67% similar
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