14 citations · 125 across the 88 of their papers we have counts for
10 papers · 1 filter
Hi-DREAM: Brain-Inspired Hierarchical Diffusion for fMRI-to-Image Reconstruction via ROI Encoder and VisuAl Mapping
Guowei Zhang, Yun Zhao, Kai Sun +4
Reconstructing natural images from fMRI requires bridging neural activity with both the structural and semantic representations used by modern generative models. Existing diffusion…
Unveiling m-Sharpness Through the Structure of Stochastic Gradient Noise
Haocheng Luo, Mehrtash Harandi, Dinh Phung +1
Sharpness-aware minimization (SAM) has emerged as a highly effective technique to improve model generalization, but its underlying principles are not fully understood. We investiga…
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…
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…
Mitigating Semantic Collapse in Generative Personalization with Test-Time Embedding Adjustment
Anh Bui, Trang Vu, Trung Le +5
In this paper, we investigate the semantic collapsing problem in generative personalization, an under-explored topic where the learned visual concept () gradually shifts from it…
Optimizing Specific and Shared Parameters for Efficient Parameter Tuning
Van-Anh Nguyen, Thanh-Toan Do, Mehrtash Harandi +2
Foundation models, with a vast number of parameters and pretraining on massive datasets, achieve state-of-the-art performance across various applications. However, efficiently adap…
Enhancing Dataset Distillation via Non-Critical Region Refinement
Minh-Tuan Tran, Trung Le, Xuan-May Le +2
Dataset distillation has become a popular method for compressing large datasets into smaller, more efficient representations while preserving critical information for model trainin…
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…
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…
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…