Datasets:

scb10x
/

ThaiOCRBench

dataset_info:
  features:
    - name: Id
      dtype: string
    - name: image
      dtype: image
    - name: Task
      dtype: string
    - name: question
      dtype: string
    - name: answer
      dtype: string
    - name: category
      dtype: string
  splits:
    - name: test
      num_bytes: 1918653929
      num_examples: 2808
  download_size: 1902027712
  dataset_size: 1918653929
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
license: cc-by-sa-4.0
task_categories:
  - image-text-to-text
language:
  - th
size_categories:
  - 1K<n<10K

ThaiOCRBench: A Task-Diverse Benchmark for Vision-Language Understanding in Thai

ThaiOCRBench is the first comprehensive benchmark for evaluating vision-language models (VLMs) on Thai text-rich visual understanding tasks.
Inspired by OCRBench v2, it contains 2,808 human-annotated samples across 13 diverse tasks, including table parsing, chart understanding, full-page OCR, key information extraction, and visual question answering.

The benchmark enables standardized zero-shot evaluation for both proprietary and open-source models, revealing significant performance gaps and paving the way for document understanding in low-resource languages.

🚀 Our paper ThaiOCRBench has been accepted to the IJCNLP-AACL 2025 Main Conference!

👉 📄 Read the Paper
👉 💻 GitHub Repository

📊 Dataset Statistics

Task Type	Number of Samples
Text Recognition	333
Table Parsing	193
Full-page OCR	197
Chart Parsing	200
Key Information Extraction	201
Diagram VQA	204
Fine-grained Text Recognition	206
Handwritten Content Extraction	209
Key Information Mapping	209
Document Parsing	211
Infographics VQA	213
Document Classification	215
Cognition VQA	217
Total	2,808

🧠 Performance of VLMs on ThaiOCRBench

📘 Citation

If you use ThaiOCRBench in your research or applications, please cite our work:

@misc{nonesung2025thaiocrbenchtaskdiversebenchmarkvisionlanguage,
      title={ThaiOCRBench: A Task-Diverse Benchmark for Vision-Language Understanding in Thai}, 
      author={Surapon Nonesung and Teetouch Jaknamon and Sirinya Chaiophat and Natapong Nitarach and Chanakan Wittayasakpan and Warit Sirichotedumrong and Adisai Na-Thalang and Kunat Pipatanakul},
      year={2025},
      eprint={2511.04479},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2511.04479}, 
}