Technology

Researchers from Meta's FAIR, INRIA, Université Paris Saclay, and Google are working on ways to automatically curate high-quality datasets to improve self-supervised learning (SSL). SSL enables models to be trained without human annotations, expanding data and model scalability, but its success often requires careful data curation. The team proposes a clustering-based technique involving hierarchical k-means…