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

• URL: http://arxiv.org/abs/2511.04479v2
• Date: Fri, 07 Nov 2025 04:50:48 GMT
• Title: ThaiOCRBench: A Task-Diverse Benchmark for Vision-Language Understanding in Thai
• Authors: Surapon Nonesung, Teetouch Jaknamon, Sirinya Chaiophat, Natapong Nitarach, Chanakan Wittayasakpan, Warit Sirichotedumrong, Adisai Na-Thalang, Kunat Pipatanakul,
• Abstract summary: ThaiOCRBench is the first comprehensive benchmark for evaluating vision-language models (VLMs) on Thai text-rich visual understanding tasks.<n>We evaluate a wide range of state-of-the-art VLMs in a zero-shot setting, spanning both proprietary and open-source systems.<n>Through detailed error analysis, we identify key challenges such as language bias, structural mismatch, and hallucinated content.
• Score: 2.4295338216682456
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present ThaiOCRBench, the first comprehensive benchmark for evaluating vision-language models (VLMs) on Thai text-rich visual understanding tasks. Despite recent progress in multimodal modeling, existing benchmarks predominantly focus on high-resource languages, leaving Thai underrepresented, especially in tasks requiring document structure understanding. ThaiOCRBench addresses this gap by offering a diverse, human-annotated dataset comprising 2,808 samples across 13 task categories. We evaluate a wide range of state-of-the-art VLMs in a zero-shot setting, spanning both proprietary and open-source systems. Results show a significant performance gap, with proprietary models (e.g., Gemini 2.5 Pro) outperforming open-source counterparts. Notably, fine-grained text recognition and handwritten content extraction exhibit the steepest performance drops among open-source models. Through detailed error analysis, we identify key challenges such as language bias, structural mismatch, and hallucinated content. ThaiOCRBench provides a standardized framework for assessing VLMs in low-resource, script-complex settings, and provides actionable insights for improving Thai-language document understanding.

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