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更新规则的改进则是直接改算子本身，外层架构仍照着近年验证有效的方案来用就行。比如线性注意力一般能写成一阶线性递归：输入通常是外积，转移矩阵默认是单位矩阵，改更新规则就是改这个转移矩阵。GLA、Mamba 把单位矩阵换成对角矩阵；DeltaNet 把它变成低秩单位矩阵；Kimi 把单位矩阵放宽为可学习的对角矩阵；RWKV-7 则用对角低秩矩阵作为转移矩阵。