14 citations · 66 across the 16 of their papers we have counts for
17 papers
Personalized Image Generation with Reasoning and Reflection
Bo Ni, Ngoc N. Tran, Qinwen Ge +10
Personalized image generation has remained narrowly focused on conditional synthesis from curated visual exemplars, rather than capturing who a user is. In practice, however, a use…
Evaluating Out-of-Distribution Robustness in Graph-Based Android Malware Classification: A New Principled Benchmark
Ngoc N. Tran, Anwar Said, Waseem Abbas +2
While graph-based Android malware classifiers report strong benchmark accuracy of over 94%, their performance sharply decreases up to 45% when exposed to previously unseen variants…
Improving Routing in Sparse Mixture of Experts with Graph of Tokens
Tam Nguyen, Ngoc N. Tran, Khai Nguyen +1
Sparse Mixture of Experts (SMoE) has emerged as a key to achieving unprecedented scalability in deep learning. By activating only a small subset of parameters per sample, SMoE achi…
PBP: Post-training Backdoor Purification for Malware Classifiers
Dung Thuy Nguyen, Ngoc N. Tran, Taylor T. Johnson +1
In recent years, the rise of machine learning (ML) in cybersecurity has brought new challenges, including the increasing threat of backdoor poisoning attacks on ML malware classifi…
Generalization Bounds for Robust Contrastive Learning: From Theory to Practice
Ngoc N. Tran, Lam Tran, Hoang Phan +5
Contrastive Learning first extracts features from unlabeled data, followed by linear probing with labeled data. Adversarial Contrastive Learning (ACL) integrates Adversarial Traini…
Sharpness & Shift-Aware Self-Supervised Learning
Ngoc N. Tran, Son Duong, Hoang Phan +3
Self-supervised learning aims to extract meaningful features from unlabeled data for further downstream tasks. In this paper, we consider classification as a downstream task in pha…
Anti-DreamBooth: Protecting users from personalized text-to-image synthesis
Thanh Van Le, Hao Phung, Thuan Hoang Nguyen +3
Text-to-image diffusion models are nothing but a revolution, allowing anyone, even without design skills, to create realistic images from simple text inputs. With powerful personal…
Multiple Perturbation Attack: Attack Pixelwise Under Different -norms For Better Adversarial Performance
Ngoc N. Tran, Anh Tuan Bui, Dinh Phung +1
Adversarial machine learning has been both a major concern and a hot topic recently, especially with the ubiquitous use of deep neural networks in the current landscape. Adversaria…
Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective
Hoang Phan, Lam Tran, Quyen Tran +6
Multi-task learning (MTL) trains deep neural networks to optimize several objectives simultaneously using a shared backbone, which leads to reduced computational costs, improved da…
Stochastic Multiple Target Sampling Gradient Descent
Hoang Phan, Ngoc Tran, Trung Le +3
Sampling from an unnormalized target distribution is an essential problem with many applications in probabilistic inference. Stein Variational Gradient Descent (SVGD) has been show…
ReINTEL Challenge 2020: A Comparative Study of Hybrid Deep Neural Network for Reliable Intelligence Identification on Vietnamese SNSs
Hoang Viet Trinh, Tung Tien Bui, Tam Minh Nguyen +4
The overwhelming abundance of data has created a misinformation crisis. Unverified sensationalism that is designed to grab the readers' short attention span, when crafted with mali…
Efficient Low-Latency Dynamic Licensing for Deep Neural Network Deployment on Edge Devices
Toan Pham Van, Ngoc N. Tran, Hoang Pham Minh +2
Along with the rapid development in the field of artificial intelligence, especially deep learning, deep neural network applications are becoming more and more popular in reality.…
From Universal Language Model to Downstream Task: Improving RoBERTa-Based Vietnamese Hate Speech Detection
Quang Huu Pham, Viet Anh Nguyen, Linh Bao Doan +2
Natural language processing is a fast-growing field of artificial intelligence. Since the Transformer was introduced by Google in 2017, a large number of language models such as BE…
Interpreting the Latent Space of Generative Adversarial Networks using Supervised Learning
Toan Pham Van, Tam Minh Nguyen, Ngoc N. Tran +4
With great progress in the development of Generative Adversarial Networks (GANs), in recent years, the quest for insights in understanding and manipulating the latent space of GAN…
Efficient Palm-Line Segmentation with U-Net Context Fusion Module
Toan Pham Van, Son Trung Nguyen, Linh Bao Doan +2
Many cultures around the world believe that palm reading can be used to predict the future life of a person. Palmistry uses features of the hand such as palm lines, hand shape, or…
Deep Learning Approach for Singer Voice Classification of Vietnamese Popular Music
Toan Pham Van, Ngoc N. Tran, Ta Minh Thanh
Singer voice classification is a meaningful task in the digital era. With a huge number of songs today, identifying a singer is very helpful for music information retrieval, music…
Deep Neural Networks based Invisible Steganography for Audio-into-Image Algorithm
Quang Pham Huu, Thoi Hoang Dinh, Ngoc N. Tran +2
In the last few years, steganography has attracted increasing attention from a large number of researchers since its applications are expanding further than just the field of infor…