MC-RFM achieves superior few-shot adaptation by representing features on a mixed hyperbolic-Euclidean manifold and learning task-conditioned continuous transport via Riemannian flow matching to hybrid prototypes.
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MC-RFM: Geometry-Aware Few-Shot Adaptation via Mixed-Curvature Riemannian Flow Matching
MC-RFM achieves superior few-shot adaptation by representing features on a mixed hyperbolic-Euclidean manifold and learning task-conditioned continuous transport via Riemannian flow matching to hybrid prototypes.