10 papers
Backdoor Attacks on Prompt-Driven Video Segmentation Foundation Models
Zongmin Zhang, Zhen Sun, Yifan Liao +5
Prompt-driven Video Segmentation Foundation Models (VSFMs), such as SAM2, are increasingly used in applications including autonomous driving and digital pathology, yet their securi…
CHASM: Unveiling Covert Advertisements on Chinese Social Media
Jingyi Zheng, Tianyi Hu, Yule Liu +5
Current benchmarks for evaluating large language models (LLMs) in social media moderation completely overlook a serious threat: covert advertisements, which disguise themselves as…
JALMBench: Benchmarking Jailbreak Vulnerabilities in Audio Language Models
Zifan Peng, Yule Liu, Zhen Sun +9
Large Audio Language Models (LALMs) have made significant progress. While increasingly deployed in real-world applications, LALMs face growing safety risks from jailbreak attacks t…
Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks
Wenhan Dong, Chao Lin, Xinlei He +2
Privacy-preserving federated learning (PPFL) aims to train a global model for multiple clients while maintaining their data privacy. However, current PPFL protocols exhibit one or…
ZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities
Wenhan Dong, Zhen Sun, Yuemeng Zhao +9
Large language models (LLMs) have demonstrated potential in educational applications, yet their capacity to accurately assess the cognitive alignment of reading materials with stud…
Thought Manipulation: External Thought Can Be Efficient for Large Reasoning Models
Yule Liu, Jingyi Zheng, Zhen Sun +6
Recent advancements in large reasoning models (LRMs) have demonstrated the effectiveness of scaling test-time computation to enhance reasoning capabilities on various tasks. Howeve…