VESTA: A Fully Automated Scenario Generation and Safety Evaluation Framework for LLM Agents 事件

VESTA: A Fully Automated Scenario Generation and Safety Evaluation Framework for LLM Agents arXiv:2606.08531v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evolving from simple text-based interaction systems into LLM agents that can maintain memory, use tools, access external environments, and execute tasks. As their capabilities and autonomy expand, the safety risks they face also become more diverse. Existing evaluations often rely on manually written scenarios,