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Rank estimation can be reliably achieved even in the presence of structured label noise by embracing the inherent uncertainty of ordinal annotations.
ConOrd redefines ordinal regression by seamlessly integrating global structure into contrastive learning, outperforming existing methods across multiple benchmarks.
