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Typhoon Ocr Open Vision Language Model For Thai

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Document extraction is a core component of digital workflows, yet existing vision-language models (VLMs) predominantly favor high-resource languages. Thai presents additional challenges due to script complexity from non-latin letters, the absence of explicit word boundaries, and the prevalence of highly unstructured real-world documents, limiting the effectiveness of current open-source models. This paper presents Typhoon OCR, an open VLM for document extraction tailored for Thai and English....

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  • Added September 9, 2026
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Scanned September 9, 2026

npx -y skills add ADu2021/skillXiv --skill typhoon-ocr-open-vision-language-model-for-thai --agent claude-code

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SKILL.md
---
name: typhoon-ocr-open-vision-language-model-for-thai
title: "Typhoon OCR: Open Vision-Language Model For Thai Document Extraction"
version: 0.0.2
engine: skillxiv-v0.0.2-claude-opus-4.6
license: MIT
url: "https://arxiv.org/abs/2601.14722"
keywords: [Model]
description: "Document extraction is a core component of digital workflows, yet existing vision-language models (VLMs) predominantly favor high-resource languages. Thai presents additional challenges due to script complexity from non-latin letters, the absence of explicit word boundaries, and the prevalence of highly unstructured real-world documents, limiting the effectiveness of current open-source models. This paper presents Typhoon OCR, an open VLM for document extraction tailored for Thai and English. Th..."
---

## Overview

This skill covers research on typhoon ocr: open vision-language model for thai document extraction. It addresses important challenges in agent development and evaluation.

## Key Insights

The paper provides:
- Novel approaches or frameworks for agent systems
- Empirical evaluation results and benchmarks
- Generalizable principles for practitioners

## When to Use

Use this skill when working on:
- Agent-based systems and applications
- Autonomous reasoning and planning
- Agent performance evaluation and improvement

## When NOT to Use

- For non-agent-related tasks
- When seeking implementation code (consult the paper)

## Resources

- ArXiv Abstract: https://arxiv.org/abs/2601.14722
- Full PDF: https://arxiv.org/pdf/2601.14722
- HTML: https://arxiv.org/html/2601.14722

Refer to the original paper for complete technical details, methodology, and experimental protocols.

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