2 citations · 8 across the 17 of their papers we have counts for
6 papers · 1 filter
Personalized Large Vision-Language Models
Chau Pham, Hoang Phan, David Doermann +1
The personalization model has gained significant attention in image generation yet remains underexplored for large vision-language models (LVLMs). Beyond generic ones, with persona…
DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image Generation
Hao Phung, Quan Dao, Trung Dao +3
We introduce a novel state-space architecture for diffusion models, effectively harnessing spatial and frequency information to enhance the inductive bias towards local features in…
Leveraging Hierarchical Taxonomies in Prompt-based Continual Learning
Quyen Tran, Hoang Phan, Minh Le +6
Humans perceive the world as a series of sequential events, which can be hierarchically organized with different levels of abstraction based on conceptual knowledge. Drawing inspir…
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning
Yijun Dong, Hoang Phan, Xiang Pan +1
We revisit data selection in a modern context of finetuning from a fundamental perspective. Extending the classical wisdom of variance minimization in low dimensions to high-dimens…
Enhancing Domain Adaptation through Prompt Gradient Alignment
Hoang Phan, Lam Tran, Quyen Tran +1
Prior Unsupervised Domain Adaptation (UDA) methods often aim to train a domain-invariant feature extractor, which may hinder the model from learning sufficiently discriminative fea…
Controllable Prompt Tuning For Balancing Group Distributional Robustness
Hoang Phan, Andrew Gordon Wilson, Qi Lei
Models trained on data composed of different groups or domains can suffer from severe performance degradation under distribution shifts. While recent methods have largely focused o…