11 citations · 16 across the 11 of their papers we have counts for
4 papers · 1 filter
DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
Changdae Oh, Yixuan Li, Kyungwoo Song +2
Adapting a pre-trained foundation model on downstream tasks should ensure robustness against distribution shifts without the need to retrain the whole model. Although existing weig…
Perturb-and-Compare Approach for Detecting Out-of-Distribution Samples in Constrained Access Environments
Heeyoung Lee, Hoyoon Byun, Changdae Oh +2
Accessing machine learning models through remote APIs has been gaining prevalence following the recent trend of scaling up model parameters for increased performance. Even though t…
Graph Perceiver IO: A General Architecture for Graph Structured Data
Seyun Bae, Hoyoon Byun, Changdae Oh +2
Multimodal machine learning has been widely studied for the development of general intelligence. Recently, the Perceiver and Perceiver IO, show competitive results for diverse data…
Learning Fair Representation via Distributional Contrastive Disentanglement
Changdae Oh, Heeji Won, Junhyuk So +4
Learning fair representation is crucial for achieving fairness or debiasing sensitive information. Most existing works rely on adversarial representation learning to inject some in…