AI RESEARCH
Real-Time Trust Verification for Safe Agentic Actions using TrustBench
arXiv CS.AI
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ArXi:2603.09157v1 Announce Type: new As large language models evolve from conversational assistants to autonomous agents, ensuring trustworthiness requires a fundamental shift from post-hoc evaluation to real-time action verification. Current frameworks like AgentBench evaluate task completion, while TrustLLM and HELM assess output quality after generation. However, none of these prevent harmful actions during agent execution.