2 citations · 2 across the 22 of their papers we have counts for
9 papers · 1 filter
Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path
Yuchen Ren, Zhengyu Zhao, Chenhao Lin +4
Transferable adversarial examples are known to cause threats in practical, black-box attack scenarios. A notable approach to improving transferability is using integrated gradients…
Nullu: Mitigating Object Hallucinations in Large Vision-Language Models via HalluSpace Projection
Le Yang, Ziwei Zheng, Boxu Chen +3
Recent studies have shown that large vision-language models (LVLMs) often suffer from the issue of object hallucinations (OH). To mitigate this issue, we introduce an efficient met…
Generalizable Targeted Data Poisoning against Varying Physical Objects
Zhizhen Chen, Zhengyu Zhao, Subrat Kishore Dutta +3
Targeted data poisoning (TDP) aims to compromise the model's prediction on a specific (test) target by perturbing a small subset of training data. Existing work on TDP has focused…
A Survey on Adversarial Machine Learning for Code Data: Realistic Threats, Countermeasures, and Interpretations
Yulong Yang, Haoran Fan, Chenhao Lin +4
Code Language Models (CLMs) have achieved tremendous progress in source code understanding and generation, leading to a significant increase in research interests focused on applyi…
An Optimizable Suffix Is Worth A Thousand Templates: Efficient Black-box Jailbreaking without Affirmative Phrases via LLM as Optimizer
Weipeng Jiang, Zhenting Wang, Juan Zhai +3
Despite prior safety alignment efforts, mainstream LLMs can still generate harmful and unethical content when subjected to jailbreaking attacks. Existing jailbreaking methods fall…
SlowPerception: Physical-World Latency Attack against Visual Perception in Autonomous Driving
Chen Ma, Ningfei Wang, Zhengyu Zhao +2
Autonomous Driving (AD) systems critically depend on visual perception for real-time object detection and multiple object tracking (MOT) to ensure safe driving. However, high laten…
A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authentication
Jingyi Deng, Chenhao Lin, Zhengyu Zhao +4
Deep generative models have demonstrated impressive performance in various computer vision applications, including image synthesis, video generation, and medical analysis. Despite…
Systematic Categorization, Construction and Evaluation of New Attacks against Multi-modal Mobile GUI Agents
Yulong Yang, Xinshan Yang, Shuaidong Li +4
The integration of Large Language Models (LLMs) and Multi-modal Large Language Models (MLLMs) into mobile GUI agents has significantly enhanced user efficiency and experience. Howe…
ControlLoc: Physical-World Hijacking Attack on Visual Perception in Autonomous Driving
Chen Ma, Ningfei Wang, Zhengyu Zhao +3
Recent research in adversarial machine learning has focused on visual perception in Autonomous Driving (AD) and has shown that printed adversarial patches can attack object detecto…