3 accepted papers
While existing AI-generated image detectors report high performance, we identify that this is largely driven by a critical *prediction asymmetry*: a bias toward the real class that severely limits sensitivity to generated content, especially under standard post-processing operations such as compress…
Large Language Models (LLMs) remain highly vulnerable to jailbreak attacks, yet existing evaluations rely primarily on outcome-level metrics such as Attack Success Rate (ASR), providing limited insight into how and why safety failures occur. We propose an explanation-aware safety framework that augm
Large language models (LLMs) are increasingly deployed in real-world applications but remain highly vulnerable to jailbreak prompts that bypass safety guardrails and elicit harmful outputs. We propose GraphShield, a graph-theoretic jailbreak detector that models information routing inside the LLM as…