JEPAMatch: Geometric Representation Shaping for Semi-Supervised Learning
arXiv:2604.21046v2 Announce Type: replace
Abstract: Semi-supervised learning has emerged as a powerful paradigm for leveraging large amounts of unlabeled data to improve the performance of machine learning models when labeled data are scarce. Among ex…