Positive and negative pairs or groups define which representations should be similar in an embedding space. The learned encoder can then support retrieval, classification, clustering, or cross-modal matching.
Contrastive learning trains representations by pulling related examples closer and pushing unrelated examples apart.
Positive and negative pairs or groups define which representations should be similar in an embedding space. The learned encoder can then support retrieval, classification, clustering, or cross-modal matching.