Researchers from New York University Introduce Symile: A General Framework for Multimodal Contrastive Learning

Contrastive learning has become essential for building representations from paired data like image-text combinations in AI. It has shown great utility in transferring learned knowledge to downstream tasks, especially in domains with complex data interdependencies, such as robotics and healthcare. In robotics, for instance, agents gather data from visual, tactile, and proprioceptive sensors, while healthcare […]

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