Benchmarks for Trajectory Safety Evaluation and Diagnosis in OpenClaw and Codex: ATBench-Claw and ATBench-Codex
As agent systems move into increasingly diverse execution settings, trajectory-level safety evaluation and diagnosis require benchmarks that evolve with them. ATBench is a diverse and realistic agent trajectory benchmark for safety evaluation and diagnosis. This report presents ATBench-Claw and ATBench-Codex, two domain-customized extensions that carry ATBench into the OpenClaw and OpenAI Codex / Codex-runtime settings. The key adaptation mechanism is to analyze each new setting, customize the three-dimensional Safety Taxonomy over risk source, failure mode, and real-world harm, and then use that customized taxonomy to define the benchmark specification consumed by the shared ATBench cons...
| Authors | Zhonghao Yang, Yu Li, Yanxu Zhu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 16 April 2026 |
| Last updated at source | 29 April 2026 |
Connected in the knowledge graph
- AI45Research/ATBench-CodexDataset · cited by
- AI45Research/ATBench-ClawDataset · cited by
Models and datasets referencing this paper
- AI45Research/ATBench-CodexDataset
- AI45Research/ATBench-ClawDataset
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