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Then they ran base contrastive learning models and models with the new algorithm through the simulations three times to see how well each classified images.

They began by using simple problem-solving techniques to construct sets of contrastive summaries -- a set of faithful, error-free summaries and a set of unfaithful summaries containing errors.

These two encoders were combined and trained using an algorithm called contrastive learning, which aims to learn useful input features and their cross-modal associations.

To create a more efficient alternative, in recent years researchers have turned to models built through a technique known as contrastive self-supervised learning.

The kinds of silences this work tests are called relative or contrastive, and they have some overlap with the study of holes.