1S-DAug: One-Shot Data Augmentation for Robust Few-Shot Generalization

arXiv:2602.00114v4 Announce Type: replace-cross Abstract: Few-shot learning (FSL) challenges model generalization to novel classes based on just a few shots of labeled examples, a testbed where traditional test-time augmentations fail to be effective. We introduce 1S-DAug, a one-shot generative...