6 papers
MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models
Linhao Luo, Thuy-Trang Vu, Van-Anh Nguyen +3
Aligning large language models (LLMs) with diverse and multifaceted user preferences is a fundamental challenge in personalized AI systems. Existing multi-objective alignment metho…
Machine Intelligence that Understands Visual and Linguistic Information and Interacts with Humans and Environments
Van Quang Nguyen
Advancements at the intersection of computer vision and natural language processing are crucial for applications like assistive tech, multimedia querying, and robotics. This disser…
Adaptive Subspace Projection for Generative Personalization
Van-Anh Nguyen, Anh Tuan Bui, Tamas Abraham +5
Generative personalization often suffers from the semantic collapsing problem (SCP), where a learned personalized concept overpowers the rest of the text prompt, causing the model…
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…
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…
Agnostic Sharpness-Aware Minimization
Van-Anh Nguyen, Quyen Tran, Tuan Truong +3
Sharpness-aware minimization (SAM) has been instrumental in improving deep neural network training by minimizing both the training loss and the sharpness of the loss landscape, lea…