Contrastive learning methods are techniques in the field of machine learning where a computer learns to recognize differences and similarities between data.
The goal is to bring similar things closer together and push different things further apart.
You can imagine it like recognizing different animals and learning which ones look similar and which are very different.
These methods help computers understand patterns without needing many examples with exact labels.
Contrastive learning is often used with images, texts, or speech to create better representations of the data.