SOURCE-LINKED INTELLIGENCE
Support Topology and Gradient Mixing in Sinkhorn Layers
Sparse Sinkhorn layers use a fixed support graph to restrict transport between tokens. How does this graph control gradient propagation through the scaling iterations. We develop a fixed-support calculus showing that each row-column cycle induces a row-stochastic operator on column-potential perturbations modulo constants. Its transpose propagates zero-mass reverse-mode cotangents. The finite-cycle operator uses two distinct half-step transport plans; at a balanced fixed point it reduces to a two-step walk determined by a single plan. We derive the accompanying score and marginal source terms
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- arXiv · AI, language, vision and robotics · 2026-09-07T20:18:56.000Z
First collected: 2026-09-20T20:32:20.942Z. This is not the publication date.