54 citations · 112 across the 11 of their papers we have counts for
3 papers · 1 filter
AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models
Sicheng Zhu, Ruiyi Zhang, Bang An +6
Safety alignment of Large Language Models (LLMs) can be compromised with manual jailbreak attacks and (automatic) adversarial attacks. Recent studies suggest that defending against…
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint
Paiheng Xu, Yuhang Zhou, Bang An +2
Given the growing concerns about fairness in machine learning and the impressive performance of Graph Neural Networks (GNNs) on graph data learning, algorithmic fairness in GNNs ha…
On the Possibilities of AI-Generated Text Detection
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu +3
Our work addresses the critical issue of distinguishing text generated by Large Language Models (LLMs) from human-produced text, a task essential for numerous applications. Despite…