新闻
ASLEval: Measuring Privacy Exposure Displacement in LLM Agent Sessions
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- ASLEval framework measures privacy leaks in multi-step LLM agent sessions, finding that standard evaluation methods miss nearly 47% of actual data exposure.
- 为何重要
- Engineers building or auditing tool-using LLM agents in enterprise environments need this to understand where private data actually escapes during agent operations.
- 注意
- The framework requires pre-registering target data and authorization rules upfront; real-world applicability depends on whether your agent architecture and tool integrations match the tested enterprise-style environments.
- agent
- llm
- eval
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