Contrastive learning benefits from generated data but can be harmed by it too.
problem Contrastive learning's reliance on data augmentation and the impact of generated data.
method Investigates the role of generated data in contrastive learning and proposes Adaptive Inflation (AdaInf).
result Generated data can sometimes harm contrastive learning, and AdaInf improves performance.