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cs.AI2026
From Expected Harmfulness to Likelihood: A Probabilistic Reformulation of Jailbreaking LLM Agents
Juanyang Xu, Zheng Wang, Xingyu Zhao +2
When the harmfulness of an LLM agent's output can be quantified, a natural jailbreaking objective is to maximize expected harmfulness over admissible input modifications. An altern…
cs.LG2026
Probabilistic Adversarial Training
Andi Zhang, Xingyu Zhao, Siddartha Khastgir
Building on a probabilistic perspective in which adversarial examples arise from the overlap between a distance-based distribution and a victim-classifier-induce…
cs.CV2026
GPO-V: Jailbreak Diffusion Vision Language Model by Global Probability Optimization
Yu Pan, Andi Zhang, Yi Wang +2
Diffusion Vision-Language Models (dVLMs), built upon the non-causal foundations of Diffusion Large Language Models (dLLMs), have demonstrated remarkable efficacy in multimodal task…