arXiv:2611.07530v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed as general-purpose conversational assistants, they must handle diverse user requests while reliably refusing harmful ones. Jailbreak attacks craft adversarial instructions or conversational contexts to elicit unsafe responses despite these safeguards.
JailBound: FOL-Guided Jailbreak Evaluation for Exploring LLM Behavioral Boundaries
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