Positive-Unlabeled Learning for Agent Safety False Alarm Auditing
cs.AI
Submitted: 2026-10-02
Updated: 2026-10-02
Sources
- TraceSafe: A Systematic Assessment of LLM Guardrails on Multi-Step Tool-Calling Trajectories
- ATBench: A Diverse and Realistic Agent Trajectory Benchmark for Safety Evaluation and Diagnosis
- AgentDoG: A Diagnostic Guardrail Framework for AI Agent Safety and Security
- Carbon Filter: Real-time Alert Triage Using Large Scale Clustering and Fast Search
- Agent-SafetyBench: Evaluating the Safety of LLM Agents
- StepGuard: Learning Step-Level Guardrails with Scalable Supervision and Safety-Utility Balancing
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems