Papers with sample-specific detection

1 papers
RLShield: Dynamic Jailbreak Detection for LLMs via Reinforced Adaptive Learning (2026.findings-acl)

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Challenge: Existing approaches to detect jailbreak prompts rely on static model components or fixed decision thresholds.
Approach: They propose a dynamic jailbreak detection framework that employs reinforcement learning for adaptive threshold selection.
Outcome: Experimental results show that the framework outperforms baselines in detection performance while maintaining high computational efficiency.

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