Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications. - Hana Satou; Alan Mitkiy (CoRR, 2024)

On the Mechanisms of Adversarial Data Augmentation for Robust and Adaptive Transfer Learning. - Hana Satou; Alan Mitkiy (CoRR, 2025)

Geometrically Regularized Transfer Learning with On-Manifold and Off-Manifold Perturbation. - Hana Satou; Alan Mitkiy; F. Monkey (CoRR, 2025)

GAMA: Geometry-Aware Manifold Alignment via Structured Adversarial Perturbations for Robust Domain Adaptation. - Hana Satou; F. Monkey (CoRR, 2025)

GAMA++: Disentangled Geometric Alignment with Adaptive Contrastive Perturbation for Reliable Domain Transfer. - Kim Yun; Hana Satou; F. Monkey (CoRR, 2025)

Dynamic Epsilon Scheduling: A Multi-Factor Adaptive Perturbation Budget for Adversarial Training. - Alan Mitkiy; James Smith; Hana Satou; Hiroshi Tanaka; Emily Johnson; F. Monkey (CoRR, 2025)

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency. - Hiroshi Tanaka; Anika Rao; Hana Satou; Michael Johnson; Sofia García (CoRR, 2025)

Learning to Fuse: Modality-Aware Adaptive Scheduling for Robust Multimodal Foundation Models. - Liam Bennett; Mason Clark; Lucas Anderson; Hana Satou; Olivia Martinez (CoRR, 2025)