PrivacyPeek is a benchmark with 1,182 cases across 7 acquisition behaviors and 16 domains that evaluates acquisition-stage privacy leakage in LLM agents, finding it widespread with limited prompt mitigation.
Mpci-bench: A benchmark for multimodal pairwise contextual integrity evaluation of language model agents
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Symbolic guardrails enforce 74% of specified safety policies in agent benchmarks and boost safety without hurting utility.
SELFCI uses complementary self-distillation with two reverse KL divergences to align LLMs to contextual integrity while preserving utility, outperforming RL baselines like GRPO in agentic settings.
citing papers explorer
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PrivacyPeek: Auditing What LLM-Based Agents Acquire, Not Just What They Say
PrivacyPeek is a benchmark with 1,182 cases across 7 acquisition behaviors and 16 domains that evaluates acquisition-stage privacy leakage in LLM agents, finding it widespread with limited prompt mitigation.
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Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility
Symbolic guardrails enforce 74% of specified safety policies in agent benchmarks and boost safety without hurting utility.
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It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs
SELFCI uses complementary self-distillation with two reverse KL divergences to align LLMs to contextual integrity while preserving utility, outperforming RL baselines like GRPO in agentic settings.