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+ # ThaiOCRBench: A Task-Diverse Benchmark for Vision-Language Understanding in Thai
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+ **ThaiOCRBench** is the first comprehensive benchmark for evaluating vision-language models (VLMs) on Thai text-rich visual understanding tasks.
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+ 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.
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+ 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.
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+ 🚀 **Our paper _ThaiOCRBench_ has been accepted to the IJCNLP-AACL 2025 Main Conference!**
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+ ## 📊 Dataset Statistics
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+ | Task Type | Number of Samples |
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+ |-------------------------------|-------------------|
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+ | Text Recognition | 333 |
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+ | Table Parsing | 193 |
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+ | Full-page OCR | 197 |
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+ | Chart Parsing | 200 |
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+ | Key Information Extraction | 201 |
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+ | Diagram VQA | 204 |
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+ | Fine-grained Text Recognition | 206 |
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+ | Handwritten Content Extraction| 209 |
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+ | Key Information Mapping | 209 |
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+ | Document Parsing | 211 |
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+ | Infographics VQA | 213 |
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+ | Document Classification | 215 |
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+ | Cognition VQA | 217 |
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+ | **Total** | **2,808** |
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+ ## 🧠 Performance of VLMs on ThaiOCRBench
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+ <p align="center">
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+ <img src="https://github.com/scb-10x/ThaiOCRBench/blob/main/pics/thaiocrbench_eval.png" width="88%" height="60%">
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+ </p>
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+ ## 📘 Citation
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+ If you use this benchmark in your research, please cite:
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