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Geodesic Flow Matching for Denoising High-Dimensional Structured Representations

arXiv cs.AI ↗ · 2026-06-02 Cached

This paper proposes Geodesic Flow Matching, a Riemannian transport method for denoising Spatial Semantic Pointers (SSPs) on toroidal manifolds, and demonstrates a 72% reduction in tracking error and 40% efficiency gain in a spiking neural SLAM system.

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