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metadata
license: apache-2.0
language:
  - zh
tags:
  - Traditional Chinese Medicine
  - Multimodal Data

๐Ÿ“š Introduction

This is the text benchmark for ShizhenGPT, a multimodal LLM for Traditional Chinese Medicine (TCM).

For details, see our paper and GitHub repository.

๐Ÿ“Š Benchmark Overview

The benchmark is composed of 7 sections, each compiled from different authoritative TCM illustrated books.

Samples
TCM Patent 1119
TCM Material 1020
TCM Herb 1100
Tongue 768
Palm 640
Holism 1011
Tuina 831
Eye 715

โš’๏ธ Data Construction

{
  "image": [
    "tcm_bench_images/0001.jpg"
  ],
  "question": "่ฏทๆ นๆฎ่ฟ™ๅผ ๅ›พ็‰‡๏ผŒๅˆคๆ–ญๅฎƒๅฑžไบŽไธ‹้ขๅ“ชไธ€็ง๏ผŸ",
  "options": {
    "A": "ๅทดๆˆŸ่‚‰",
    "B": "็›ๅทดๆˆŸๅคฉ",
    "C": "ๅˆถ็™ฝ้™„ๅญ็‰‡",
    "D": "็”Ÿ็™ฝ้™„ๅญ็‰‡"
  },
  "answer": "ๅทดๆˆŸ่‚‰",
  "answer_idx": "A",
  "category": "TCM Patent"
}

๐Ÿ“– Citation

If you find our data useful, please consider citing our work!

@misc{chen2025shizhengptmultimodalllmstraditional,
      title={ShizhenGPT: Towards Multimodal LLMs for Traditional Chinese Medicine}, 
      author={Junying Chen and Zhenyang Cai and Zhiheng Liu and Yunjin Yang and Rongsheng Wang and Qingying Xiao and Xiangyi Feng and Zhan Su and Jing Guo and Xiang Wan and Guangjun Yu and Haizhou Li and Benyou Wang},
      year={2025},
      eprint={2508.14706},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2508.14706},
}