Sinkhorn-normalized doubly stochastic attention preserves rank more effectively than Softmax row-stochastic attention, with both showing doubly exponential rank decay to one with network depth.
Lipschitz networks and distributional robustness
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Sinkhorn doubly stochastic attention rank decay analysis
Sinkhorn-normalized doubly stochastic attention preserves rank more effectively than Softmax row-stochastic attention, with both showing doubly exponential rank decay to one with network depth.