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20232026
most citedEnhancing Domain Adaptation through Prompt Gradient Alignment

2 citations · 10 across the 25 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation

Tung-Long Vuong, Hoang Phan, Vy Vo +4

Recent approaches leveraging multi-modal pre-trained models like CLIP for Unsupervised Domain Adaptation (UDA) have shown significant promise in bridging domain gaps and improving…

cs.LG2025

Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models

Ngoc-Quan Pham, Tuan Truong, Quyen Tran +3

We introduce Interactive Bayesian Distributional Robustness (IBDR), a novel Bayesian inference framework that allows modeling the interactions between particles, thereby enhancing…

cs.LG2025

Why Domain Generalization Fail? A View of Necessity and Sufficiency

Long-Tung Vuong, Vy Vo, Hien Dang +5

Despite a strong theoretical foundation, empirical experiments reveal that existing domain generalization (DG) algorithms often fail to consistently outperform the ERM baseline. We…

cs.LG2025★ 1 cited

Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization

Haocheng Luo, Tuan Truong, Tung Pham +3

Sharpness-Aware Minimization (SAM) has attracted significant attention for its effectiveness in improving generalization across various tasks. However, its underlying principles re…

cs.LG2025

Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them

Anh Bui, Trang Vu, Long Vuong +5

Concept erasure has emerged as a promising technique for mitigating the risk of harmful content generation in diffusion models by selectively unlearning undesirable concepts. The c…