1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2026
Skeletonization-Based Adversarial Perturbations on Large Vision Language Model's Mathematical Text Recognition
Masatomo Yoshida, Haruto Namura, Nicola Adami +1
This work explores the visual capabilities and limitations of foundation models by introducing a novel adversarial attack method utilizing skeletonization to reduce the search spac…
cs.AI2026★ 1 cited
Integrating Distribution Matching into Semi-Supervised Contrastive Learning for Labeled and Unlabeled Data
Shogo Nakayama, Masahiro Okuda
The advancement of deep learning has greatly improved supervised image classification. However, labeling data is costly, prompting research into unsupervised learning methods such…