PsychCounsel-Bench is a benchmark dataset designed to evaluate the psychological intelligence of Large Language Models (LLMs).
The dataset is inspired by the U.S. National Counselor Examination (NCE) — a professional licensure exam for counselors — and aims to assess whether LLMs possess the psychological knowledge and reasoning abilities required for counseling-related tasks.

This repository provides a partial release of the PsychCounsel-Bench dataset.
The full dataset will be publicly released after the acceptance of the associated research paper.

• Total questions (full version): 2,252
• Current release: Partial subset
• Format: Multiple-choice (single correct answer: A/B/C/D)
• Language: English

Each entry follows this structure:

 {
    "id": 3,
    "question": "An individual's self-esteem is most likely to improve when they credit their success to which of the following?",
    "options": {
      "a": "Factors within themselves",
      "b": "Factors outside themselves",
      "c": "Indirect factors",
      "d": "Random factors",
      "e": "Unstable factors"
    },
    "answer": "a"
  }

This dataset is released under the CC BY-NC-ND 4.0 license.
You are free to share — copy and redistribute the material in any medium or format — under the following terms:

📘 Full license text:
Creative Commons CC BY-NC-ND 4.0

If you use this dataset in your research, please cite:

@article{zeng2025pychobench,
  title={PsychCounsel-Bench: Evaluating the Psychology Intelligence of Large Language Models},
  author={Zeng, Min},
  journal={arXiv preprint arXiv:2510.01611},
  year={2025}
}