Self-WeightedContrastiveLearningamongMultiple ViewsforMitigatingRepresentationDegeneration

Furthermore, [30, 31] pointed out to conduct CL with reconstruction regularization to achieve robust representations for downstream tasks. RINCE [15] (a short name of Robust InfoNCE) is a variant of InfoNCE contrastive loss that considers noise in false positive sample pairs.