5 papers
OOD-MMSafe: Advancing MLLM Safety from Harmful Intent to Hidden Consequences
Ming Wen, Kun Yang, Jingyu Zhang +4
While safety alignment for Multimodal Large Language Models (MLLMs) has gained significant attention, current paradigms primarily target malicious intent or situational violations.…
Pragma-VL: Towards a Pragmatic Arbitration of Safety and Helpfulness in MLLMs
Ming Wen, Kun Yang, Xin Chen +4
Multimodal Large Language Models (MLLMs) pose critical safety challenges, as they are susceptible not only to adversarial attacks such as jailbreaking but also to inadvertently gen…
PerProb: Indirectly Evaluating Memorization in Large Language Models
Yihan Liao, Jacky Keung, Xiaoxue Ma +2
The rapid advancement of Large Language Models (LLMs) has been driven by extensive datasets that may contain sensitive information, raising serious privacy concerns. One notable th…
Exposing and Defending Membership Leakage in Vulnerability Prediction Models
Yihan Liao, Jacky Keung, Xiaoxue Ma +2
Neural models for vulnerability prediction (VP) have achieved impressive performance by learning from large-scale code repositories. However, their susceptibility to Membership Inf…
Chart2Code-MoLA: Efficient Multi-Modal Code Generation via Adaptive Expert Routing
Yifei Wang, Jacky Keung, Zhenyu Mao +2
Chart-to-code generation is a critical task in automated data visualization, translating complex chart structures into executable programs. While recent Multi-modal Large Language…