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paperApril 2026Unreviewed

OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language Environment Simulation

Xiaomeng Hu, Yinger Zhang, Fei Huang, Jianhong Tu, Yang Su, Lianghao Deng, Yuxuan Liu, Yantao Liu, Dayiheng Liu, Tsung-Yi Ho

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Abstract

AI agents are expected to perform professional work across hundreds of occupational domains (from emergency department triage to nuclear reactor safety monitoring to customs import processing), yet existing benchmarks can only evaluate agents in the few domains where public environments exist. We introduce OccuBench, a benchmark covering 100 real-world professional task scenarios across 10 industry categories and 65 specialized domains, enabled by Language Environment Simulators (LESs) that simu

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Monitoring & DetectionBenchmarks & Evaluation

Cite

@misc{hu2026occubench,
  title = {{OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language Environment Simulation}},
  author = {Xiaomeng Hu and Yinger Zhang and Fei Huang and Jianhong Tu and Yang Su and Lianghao Deng and Yuxuan Liu and Yantao Liu and Dayiheng Liu and Tsung-Yi Ho},
  year = {2026},
  month = apr,
  eprint = {2604.10866},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.10866}
}