A soft-weighted contrastive loss using rank-gap affinity and disparity terms learns globally consistent ordinal embeddings and reaches SOTA on age, BIQA, and BVQA benchmarks.
SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
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Contrastive Order Learning: A General Framework for Ordinal Regression
A soft-weighted contrastive loss using rank-gap affinity and disparity terms learns globally consistent ordinal embeddings and reaches SOTA on age, BIQA, and BVQA benchmarks.