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README.md

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-license: cc-by-nc-4.0
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+---
+license: cc-by-nc-4.0
+---
+# K-DTCBench
+
+We introduce **K-DTCBench**, a newly developed Korean benchmark featuring both computer-generated and handwritten documents, tables, and charts.
+It consists of 80 questions for each image type and two questions per image, summing up to 240 questions in total.
+This benchmark is designed to evaluate whether vision-language models can process images in different formats and be applicable for diverse domains.
+All images are generated with made-up values and statements for evaluation purposes only. We scanned hand-written documents/tables/charts, or created digital objects with matplotlib library to build K-DTCBench.
+The proportions of digital and hand-written images are equal, each constituting 50%.
+
+
+For more details, Please refer to the [VARCO-VISION technical report(Coming Soon)]().
+
+<table>
+<tr>
+  <th>Category</th>
+  <th>Image</th>
+  <th>K-DTCBench</th>
+</tr>
+<tr>
+  <td align="center">document</td>
+  <td width=350><img src="https://cdn-uploads.huggingface.co/production/uploads/624ceaa38746b2f5773c2d1c/Ipi4HR73P-PDC5XcgP3WF.png"></td>
+  <td>
+    <strong>question:</strong> 보고서의 주요 내용이 아닌 것은 무엇인가요?
+    <br>
+    <strong>A:</strong> 안전 인프라 확충
+    <br>
+    <strong>B:</strong> 재난 및 사고 예방 체계 구축
+    <br>
+    <strong>C:</strong> 시민 안전 교육 강화
+    <br>
+    <strong>D:</strong> 긴급 대응 시스템 개선
+  </td>
+</tr>
+<tr>
+  <td align="center">table</td>
+  <td width=350><img src="https://cdn-uploads.huggingface.co/production/uploads/624ceaa38746b2f5773c2d1c/dz_FuPnpZ5P4P3LEB5PZ0.png"></td>
+  <td>
+    <strong>question:</strong> 인프라 구축 항목의 점수는 몇 점인가요?
+    <br>
+    <strong>A:</strong> 4
+    <br>
+    <strong>B:</strong> 6
+    <br>
+    <strong>C:</strong> 8
+    <br>
+    <strong>D:</strong> 10
+  </td>
+</tr>
+<tr>
+  <td align="center">chart</td>
+  <td width=350><img src="https://cdn-uploads.huggingface.co/production/uploads/624ceaa38746b2f5773c2d1c/IbNMPPgd974SbCAsz6zIS.png"></td>
+  <td>
+    <strong>question:</strong> 직장인들이 퇴근 후 두 번째로 선호하는 활동은 무엇인가요?
+    <br>
+    <strong>A:</strong> 운동
+    <br>
+    <strong>B:</strong> 여가활동
+    <br>
+    <strong>C:</strong> 자기개발
+    <br>
+    <strong>D:</strong> 휴식
+  </td>
+</tr>
+</table>
+<br>
+
+## Inference Prompt
+```
+<image>
+{question}
+Options: A: {A}, B: {B}, C: {C}, D: {D}
+주어진 선택지 중 해당 옵션의 문자로 직접 답하세요.
+```
+
+<br>
+
+## Results
+Below are the evaluation results of various vision-language models, including [VARCO-VISION-14B]() on K-DTCBench.
+
+| | VARCO-VISION-14B | Pangea-7B | Pixtral-12B | Molmo-7B-D | Qwen2-VL-7B-Instruct | LLaVA-One-Vision-7B |
+| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
+| K-DTCBench | **84.58** | 48.33 | 27.50 | 45.83 | 75.00 | 52.91 |
+
+<br>
+
+## Citation
+(bibtex will be updated soon..) If you use K-DTCBench in your research, please cite the following:
+```
+```