3 citations · 5 across the 14 of their papers we have counts for
6 papers · 1 filter
Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models
Zhang Wei, Hanxuan Chen, Peilu Hu +19
Red-teaming is becoming a central part of large language model (LLM) safety evaluation, yet current practice still relies heavily on expert-written prompts or fixed benchmark suite…
Attention-Guided Patch-Wise Sparse Adversarial Attacks on Vision-Language-Action Models
Naifu Zhang, Wei Tao, Xi Xiao +5
In recent years, Vision-Language-Action (VLA) models in embodied intelligence have developed rapidly. However, existing adversarial attack methods require costly end-to-end trainin…
FeatureFool: Zero-Query Fooling of Video Models via Feature Map
Duoxun Tang, Xi Xiao, Guangwu Hu +6
The vulnerability of deep neural networks (DNNs) has been preliminarily verified. Existing black-box adversarial attacks usually require multi-round interaction with the model and…
MA-CBP: A Criminal Behavior Prediction Framework Based on Multi-Agent Asynchronous Collaboration
Cheng Liu, Daou Zhang, Tingxu Liu +7
With the acceleration of urbanization, criminal behavior in public scenes poses an increasingly serious threat to social security. Traditional anomaly detection methods based on fe…
SlideCoder: Layout-aware RAG-enhanced Hierarchical Slide Generation from Design
Wenxin Tang, Jingyu Xiao, Wenxuan Jiang +8
Manual slide creation is labor-intensive and requires expert prior knowledge. Existing natural language-based LLM generation methods struggle to capture the visual and structural n…
Transferability of Adversarial Attacks in Video-based MLLMs: A Cross-modal Image-to-Video Approach
Linhao Huang, Xue Jiang, Zhiqiang Wang +5
Video-based multimodal large language models (V-MLLMs) have shown vulnerability to adversarial examples in video-text multimodal tasks. However, the transferability of adversarial…