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cs.LG2026
Continual Data Unlearning in Diffusion Models via Transition-based Regularization
Sunbeom Jeong, Sehwan Kim, Sangwoo Hong +1
Data unlearning in diffusion models aims to remove the influence of specific training examples without suppressing the broader concepts they represent. However, when deletion reque…
cs.LG2025
Constructing Fair Latent Space for Intersection of Fairness and Explainability
Hyungjun Joo, Hyeonggeun Han, Sehwan Kim +2
As the use of machine learning models has increased, numerous studies have aimed to enhance fairness. However, research on the intersection of fairness and explainability remains i…
cs.LG2024
Mitigating Spurious Correlations via Disagreement Probability
Hyeonggeun Han, Sehwan Kim, Hyungjun Joo +2
Models trained with empirical risk minimization (ERM) are prone to be biased towards spurious correlations between target labels and bias attributes, which leads to poor performanc…