78 citations · 151 across the 9 of their papers we have counts for
9 papers
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention
Jie Ren, Yaxin Li, Shenglai Zeng +4
Recent advancements in text-to-image diffusion models have demonstrated their remarkable capability to generate high-quality images from textual prompts. However, increasing resear…
Exploring Memorization in Fine-tuned Language Models
Shenglai Zeng, Yaxin Li, Jie Ren +7
Large language models (LLMs) have shown great capabilities in various tasks but also exhibited memorization of training data, raising tremendous privacy and copyright concerns. Whi…
Enhancing Adversarial Training with Feature Separability
Yaxin Li, Xiaorui Liu, Han Xu +2
Deep Neural Network (DNN) are vulnerable to adversarial attacks. As a countermeasure, adversarial training aims to achieve robustness based on the min-max optimization problem and…
Trustworthy AI: A Computational Perspective
Haochen Liu, Yiqi Wang, Wenqi Fan +6
In the past few decades, artificial intelligence (AI) technology has experienced swift developments, changing everyone's daily life and profoundly altering the course of human soci…
Imbalanced Adversarial Training with Reweighting
Wentao Wang, Han Xu, Xiaorui Liu +3
Adversarial training has been empirically proven to be one of the most effective and reliable defense methods against adversarial attacks. However, almost all existing studies abou…
Elastic Graph Neural Networks
Xiaorui Liu, Wei Jin, Yao Ma +5
While many existing graph neural networks (GNNs) have been proven to perform -based graph smoothing that enforces smoothness globally, in this work we aim to further enhanc…
To be Robust or to be Fair: Towards Fairness in Adversarial Training
Han Xu, Xiaorui Liu, Yaxin Li +2
Adversarial training algorithms have been proved to be reliable to improve machine learning models' robustness against adversarial examples. However, we find that adversarial train…
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
Yaxin Li, Wei Jin, Han Xu +1
DeepRobust is a PyTorch adversarial learning library which aims to build a comprehensive and easy-to-use platform to foster this research field. It currently contains more than 10…
Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies
Wei Jin, Yaxin Li, Han Xu +4
Deep neural networks (DNNs) have achieved significant performance in various tasks. However, recent studies have shown that DNNs can be easily fooled by small perturbation on the i…