9 citations · 14 across the 6 of their papers we have counts for
6 papers
On the Mechanisms of Collaborative Learning in VAE Recommenders
Tung-Long Vuong, Julien Monteil, Hien Dang +3
Variational Autoencoders (VAEs) are a powerful alternative to matrix factorization for recommendation. A common technique in VAE-based collaborative filtering (CF) consists in appl…
Task-Driven Discrete Representation Learning
Tung-Long Vuong
In recent years, deep discrete representation learning (DRL) has achieved significant success across various domains. Most DRL frameworks (e.g., the widely used VQ-VAE and its vari…
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…
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…
Vector Quantized Wasserstein Auto-Encoder
Tung-Long Vuong, Trung Le, He Zhao +4
Learning deep discrete latent presentations offers a promise of better symbolic and summarized abstractions that are more useful to subsequent downstream tasks. Inspired by the sem…
Uncertainty-aware Model-based Policy Optimization
Tung-Long Vuong, Kenneth Tran
Model-based reinforcement learning has the potential to be more sample efficient than model-free approaches. However, existing model-based methods are vulnerable to model bias, whi…