23 citations · 52 across the 11 of their papers we have counts for
11 papers
EPIC: Explicit Posterior Item Conditioning for Semantic ID Diffusion Recommendation
Tuan-Binh Tran, Thanh Tam Nguyen, Quoc Viet Hung Nguyen +3
Semantic ID (SID) generative recommendation predicts the next item by generating a short tuple of discrete tokens. Recent masked-diffusion methods improve this process through bidi…
Towards Efficient Communication and Secure Federated Recommendation System via Low-rank Training
Ngoc-Hieu Nguyen, Tuan-Anh Nguyen, Tuan Nguyen +3
Federated Recommendation (FedRec) systems have emerged as a solution to safeguard users' data in response to growing regulatory concerns. However, one of the major challenges in th…
A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models
Cuong Dang, Dung D. Le, Thai Le
Existing works have shown that fine-tuned textual transformer models achieve state-of-the-art prediction performances but are also vulnerable to adversarial text perturbations. Tra…
Detecting Out-of-Distribution Objects through Class-Conditioned Inpainting
Quang-Huy Nguyen, Jin Peng Zhou, Zhenzhen Liu +4
Recent object detectors have achieved impressive accuracy in identifying objects seen during training. However, real-world deployment often introduces novel and unexpected objects,…
Controllable Expensive Multi-objective Learning with Warm-starting Bayesian Optimization
Quang-Huy Nguyen, Long P. Hoang, Hoang V. Viet +1
Pareto Set Learning (PSL) is a promising approach for approximating the entire Pareto front in multi-objective optimization (MOO) problems. However, existing derivative-free PSL me…
A Framework for Controllable Pareto Front Learning with Completed Scalarization Functions and its Applications
Tran Anh Tuan, Long P. Hoang, Dung D. Le +1
Pareto Front Learning (PFL) was recently introduced as an efficient method for approximating the entire Pareto front, the set of all optimal solutions to a Multi-Objective Optimiza…
Improving Pareto Front Learning via Multi-Sample Hypernetworks
Long P. Hoang, Dung D. Le, Tran Anh Tuan +1
Pareto Front Learning (PFL) was recently introduced as an effective approach to obtain a mapping function from a given trade-off vector to a solution on the Pareto front, which sol…
Enhancing Few-shot Image Classification with Cosine Transformer
Quang-Huy Nguyen, Cuong Q. Nguyen, Dung D. Le +1
This paper addresses the few-shot image classification problem, where the classification task is performed on unlabeled query samples given a small amount of labeled support sample…
Fast Approximation of the Generalized Sliced-Wasserstein Distance
Dung Le, Huy Nguyen, Khai Nguyen +2
Generalized sliced Wasserstein distance is a variant of sliced Wasserstein distance that exploits the power of non-linear projection through a given defining function to better cap…
Improving Transformers with Probabilistic Attention Keys
Tam Nguyen, Tan M. Nguyen, Dung D. Le +5
Multi-head attention is a driving force behind state-of-the-art transformers, which achieve remarkable performance across a variety of natural language processing (NLP) and compute…
Entropic Gromov-Wasserstein between Gaussian Distributions
Khang Le, Dung Le, Huy Nguyen +3
We study the entropic Gromov-Wasserstein and its unbalanced version between (unbalanced) Gaussian distributions with different dimensions. When the metric is the inner product, whi…