3 papers
cs.LG2025
GradMix: Gradient-based Selective Mixup for Robust Data Augmentation in Class-Incremental Learning
Minsu Kim, Seong-Hyeon Hwang, Steven Euijong Whang
In the context of continual learning, acquiring new knowledge while maintaining previous knowledge presents a significant challenge. Existing methods often use experience replay te…
cs.LG2025
MIDAS: Misalignment-based Data Augmentation Strategy for Imbalanced Multimodal Learning
Seong-Hyeon Hwang, Soyoung Choi, Steven Euijong Whang
Multimodal models often over-rely on dominant modalities, failing to achieve optimal performance. While prior work focuses on modifying training objectives or optimization procedur…
cs.LG2025
T-CIL: Temperature Scaling using Adversarial Perturbation for Calibration in Class-Incremental Learning
Seong-Hyeon Hwang, Minsu Kim, Steven Euijong Whang
We study model confidence calibration in class-incremental learning, where models learn from sequential tasks with different class sets. While existing works primarily focus on acc…