5 papers
Open Models, Open Risks: Measuring Unsafe Generation in Text-to-Image Models In the Wild
Peilin Han, Yang Liu, Yilong Yang +4
Existing safety studies on text-to-image (T2I) jailbreaks are largely conducted in controlled in-the-lab settings, typically on a small number of canonical models. As a result, the…
Benign Inputs, Harmful Outputs: Cross-Modal Jailbreaking via Distributed Semantic Recomposition
Yani Wang, Yilong Yang, Yang Liu +3
Multimodal Large Language Models (MLLMs) have recently demonstrated remarkable capabilities in content synthesis and autonomous reasoning. Previous safety guardrails are primarily…
On the Generation and Mitigation of Harmful Geometry in Image-to-3D Models
Yule Liu, Yilong Yang, Jiale Teng +11
Recent advances in image-to-3D models have significantly improved the fidelity and accessibility of 3D content creation. Such a powerful reconstruction capability that enables crea…
Improving Sustainability of Adversarial Examples in Class-Incremental Learning
Taifeng Liu, Xinjing Liu, Liangqiu Dong +3
Current adversarial examples (AEs) are typically designed for static models. However, with the wide application of Class-Incremental Learning (CIL), models are no longer static and…
Auditing Data Membership in Reinforcement Learning With Verifiable Rewards
Yule Liu, Heyi Zhang, Jinyi Zheng +6
Reinforcement Learning with Verifiable Rewards (RLVR) has become a core training stage in recent large language models (LLMs). Its reliance on non-public, high-value prompt sets ra…