OpenART: Scaling Agent Red Teaming via Open-Ended Environment Evolution
- 类型:arxiv
- 标识:2608.00677
- 链接:https://arxiv.org/abs/2608.00677
- 主分类:agent
- 形态:benchmark
- 被引:0
- 被引来源:Semantic Scholar
- S2被引:0
- 影响力被引:0
- TLDR:This work proposes the Evolutionary Markov Hypergraph Attack (EMHA), a black-box policy that performs feedback-driven environment evolution by coordinating authorized state transitions without requiring parameter updates, and establishes OpenART as a scalable foundation for studying agent safety in complex, evolving environments.
- 副分类:risk
- 待LLM分类:否
- 标题中文:OpenART:通过开放式环境演化扩展 Agent 红队测试
- TLDR中文:本文提出进化式马尔可夫超图攻击(EMHA),这是一种黑盒策略,通过协调授权状态转移执行反馈驱动的环境演化,无需参数更新,并将 OpenART 确立为在复杂演化环境中研究 Agent 安全性的可扩展基础。
- 来源文件:
- /inbox/tom/_candidates/2026-08-13-agent-rag-longcontext-candidates.json
- [S2 enrich]