OpenART: Scaling Agent Red Teaming via Open-Ended Environment Evolution
AI agents operate in persistent environments where early state changes can influence decisions far into the future. Unlike conventional language-model interactions, agent behavior is mediated through a shared state that is repeatedly modified and reused across long-horizon workflows. Current safety benchmarks often fail to capture these cumulative risks because they focus on short, static tasks. To address these limitations, we introduce OpenART, an open-ended arena for scalable agent red teamin
Record details
Published: 1 August 2026
Source: arXiv red teaming query
Category: Research
Topics: Safety & alignment · Agents & autonomy · Environment
Retrieved: 4 August 2026
Related evidence
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How to cite this record
ethics.ai (1 August 2026), “OpenART: Scaling Agent Red Teaming via Open-Ended Environment Evolution,” evidence record 16172, https://ethics.ai/record/16172 (originally published by arXiv red teaming query).
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