Datasets:
metadata
dataset_info:
- config_name: accounting
features:
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- config_name: arts
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- config_name: biology
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- config_name: chinese_literature
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- config_name: dentistry
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- config_name: fundamentals_of_physical_therapy
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- config_name: mathematics
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- config_name: mechanics
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- config_name: medical
features:
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- config_name: music
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- config_name: natural_science
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- config_name: navigation
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- config_name: pharmaceutical_chemistry
features:
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- config_name: physics
features:
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dataset_size: 1283079
- config_name: sociology
features:
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- name: val
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- config_name: statistics
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- name: val
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- config_name: structural_engineering
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- name: val
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- name: dev
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- config_name: veterinary_medicine
features:
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- name: dev
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dataset_size: 5030818
configs:
- config_name: accounting
data_files:
- split: test
path: accounting/test-*
- split: val
path: accounting/val-*
- split: dev
path: accounting/dev-*
- config_name: arts
data_files:
- split: test
path: arts/test-*
- split: val
path: arts/val-*
- split: dev
path: arts/dev-*
- config_name: biology
data_files:
- split: test
path: biology/test-*
- split: val
path: biology/val-*
- split: dev
path: biology/dev-*
- config_name: chemistry
data_files:
- split: test
path: chemistry/test-*
- split: val
path: chemistry/val-*
- split: dev
path: chemistry/dev-*
- config_name: chinese_literature
data_files:
- split: test
path: chinese_literature/test-*
- split: val
path: chinese_literature/val-*
- split: dev
path: chinese_literature/dev-*
- config_name: dentistry
data_files:
- split: test
path: dentistry/test-*
- split: val
path: dentistry/val-*
- split: dev
path: dentistry/dev-*
- config_name: electronic_circuits
data_files:
- split: test
path: electronic_circuits/test-*
- split: val
path: electronic_circuits/val-*
- split: dev
path: electronic_circuits/dev-*
- config_name: fundamentals_of_physical_therapy
data_files:
- split: test
path: fundamentals_of_physical_therapy/test-*
- split: val
path: fundamentals_of_physical_therapy/val-*
- split: dev
path: fundamentals_of_physical_therapy/dev-*
- config_name: geography
data_files:
- split: val
path: geography/val-*
- split: dev
path: geography/dev-*
- split: test
path: geography/test-*
- config_name: mathematics
data_files:
- split: test
path: mathematics/test-*
- split: val
path: mathematics/val-*
- split: dev
path: mathematics/dev-*
- config_name: mechanics
data_files:
- split: test
path: mechanics/test-*
- split: val
path: mechanics/val-*
- split: dev
path: mechanics/dev-*
- config_name: medical
data_files:
- split: test
path: medical/test-*
- split: val
path: medical/val-*
- split: dev
path: medical/dev-*
- config_name: music
data_files:
- split: test
path: music/test-*
- split: val
path: music/val-*
- split: dev
path: music/dev-*
- config_name: natural_science
data_files:
- split: test
path: natural_science/test-*
- split: val
path: natural_science/val-*
- split: dev
path: natural_science/dev-*
- config_name: navigation
data_files:
- split: test
path: navigation/test-*
- split: val
path: navigation/val-*
- split: dev
path: navigation/dev-*
- config_name: pharmaceutical_chemistry
data_files:
- split: test
path: pharmaceutical_chemistry/test-*
- split: val
path: pharmaceutical_chemistry/val-*
- split: dev
path: pharmaceutical_chemistry/dev-*
- config_name: physics
data_files:
- split: test
path: physics/test-*
- split: val
path: physics/val-*
- split: dev
path: physics/dev-*
- config_name: sociology
data_files:
- split: test
path: sociology/test-*
- split: val
path: sociology/val-*
- split: dev
path: sociology/dev-*
- config_name: statistics
data_files:
- split: test
path: statistics/test-*
- split: val
path: statistics/val-*
- split: dev
path: statistics/dev-*
- config_name: structural_engineering
data_files:
- split: test
path: structural_engineering/test-*
- split: val
path: structural_engineering/val-*
- split: dev
path: structural_engineering/dev-*
- config_name: veterinary_medicine
data_files:
- split: test
path: veterinary_medicine/test-*
- split: val
path: veterinary_medicine/val-*
- split: dev
path: veterinary_medicine/dev-*
task_categories:
- text-generation
language:
- zh
tags:
- taiwan
- vlm
- traditional-chinese
- benchmark
- zh-hant
VisTW-MCQ : Visual Multi-Choice Question answering
VisTW-MCQ, composed of past examination questions from various educational levels in Taiwan, ranging from primary and secondary education to specialized undergraduate courses, such as veterinary medicine.
Our benchmark dataset was constructed using real-world exam papers collected from publicly available sources spanning the years 2013 to 2024. We selected subjects specifically requiring visual comprehension, such as medical diagnostics (e.g., interpreting X-ray and ultrasound images), geometry, electronic circuit design, and chemistry. For each question, we additionally collected human performance data, including average accuracy scores, to better gauge question difficulty and establish a human performance baseline.
Official benchmark : Github TMMMU-Benchmark/evaluation
Arxiv : VisTW: Benchmarking Vision-Language Models for Traditional Chinese in Taiwan
| Model | MCQA Score | MCQA Rank | Freeform Score | Freeform Rank | Avg Rank |
|---|---|---|---|---|---|
| gemini-2.5-flash | 0.7849 | 1 | 2.5496 | 44 | 22.5 |
| o3-2025-04-16 | 0.7769 | 2 | 6.9878 | 2 | 2.0 |
| o4-mini-2025-04-16 | 0.7364 | 3 | 6.7802 | 3 | 3.0 |
| quasar-alpha | 0.6673 | 4 | 6.2733 | 10 | 7.0 |
| 0.6619 | 5 | 6.7237 | 4 | 4.5 | |
| gemini-2.0-flash-001 | 0.6596 | 6 | 6.6451 | 6 | 6.0 |
| llama-4-maverick | 0.6529 | 7 | 4.884 | 17 | 12.0 |
| gpt-4.1 | 0.6503 | 8 | 6.5954 | 7 | 7.5 |
| optimus-alpha | 0.6434 | 9 | 6.6916 | 5 | 7.0 |
| gemini-2.5-pro-preview-03-25 | 0.6072 | 10 | 7.9725 | 1 | 5.5 |
| claude-3-5-sonnet-20241022 | 0.6019 | 11 | 5.9603 | 14 | 12.5 |
| gpt-4.1-mini | 0.5809 | 12 | 6.1344 | 11 | 11.5 |
| gpt-4o-2024-11-20 | 0.5755 | 13 | 6.1176 | 12 | 12.5 |
| qwen2.5-vl-72b-instruct | 0.5504 | 14 | 4.8656 | 18 | 16.0 |
| llama-4-scout | 0.5292 | 15 | 4.0943 | 28 | 21.5 |
| gemini-2.0-flash-lite-preview-02-05 | 0.4992 | 16 | 6.4159 | 9 | 12.5 |
| qwen2.5-vl-32b-instruct | 0.4935 | 17 | 5.5027 | 15 | 16.0 |
| gemma-3-12b-it | 0.4863 | 18 | 3.9403 | 29 | 23.5 |
| mistral-small-3.1-24b-instruct-2503 | 0.459 | 19 | 4.3298 | 22 | 20.5 |
| gemini-1.5-pro | 0.4417 | 20 | 5.0504 | 16 | 18.0 |
| gemma-3-27b-it | 0.4375 | 21 | 4.6 | 20 | 20.5 |
| meta-llama-Llama-3.2-90B-Vision-Instruct-Turbo | 0.4119 | 22 | 3.4443 | 36 | 29.0 |
| qvq-72b-preview | 0.4094 | 23 | 3.6122 | 33 | 28.0 |
| gpt-4o-mini-2024-07-18 | 0.4091 | 24 | 4.7405 | 19 | 21.5 |
| gpt-4o-2024-08-06 | 0.4 | 25 | 5.9756 | 13 | 19.0 |
| gpt-4.1-nano | 0.3974 | 26 | 4.1634 | 27 | 26.5 |
| gemini-1.5-flash | 0.3943 | 27 | 4.2611 | 23 | 25.0 |
| gemini-2.0-flash-thinking-exp-1219 | 0.3764 | 28 | 6.5053 | 8 | 18.0 |
| Qwen-Qwen2.5-VL-7B-Instruct | 0.3592 | 29 | 4.542 | 21 | 25.0 |
| OpenGVLab-InternVL2-8B-MPO | 0.3533 | 30 | 3.6778 | 32 | 31.0 |
| OpenGVLab-InternVL2_5-8B | 0.3447 | 31 | 3.9008 | 30 | 30.5 |
| OpenGVLab-InternVL2-8B | 0.3431 | 32 | 3.4504 | 35 | 33.5 |
| nova-lite-v1 | 0.3377 | 33 | 3.2626 | 37 | 35.0 |
| claude-3-haiku-20240307 | 0.3291 | 34 | 3.6992 | 31 | 32.5 |
| OpenGVLab-InternVL2_5-4B | 0.3291 | 35 | 3.6031 | 34 | 34.5 |
| gemini-1.5-flash-8b | 0.328 | 36 | 4.1771 | 26 | 31.0 |
| gemma-3n-e4b-it | 0.3264 | 37 | 2.2275 | 46 | 41.5 |
| meta-llama-Llama-3.2-11B-Vision-Instruct-Turbo | 0.3262 | 38 | 2.5786 | 43 | 40.5 |
| deepseek-ai-deepseek-vl2-small | 0.3181 | 39 | 0.5084 | 51 | 45.0 |
| llama3.2-ffm-11b-v-32k-chat | 0.3119 | 40 | 3.115 | 39 | 39.5 |
| OpenGVLab-InternVL2-4B | 0.3081 | 41 | 2.3069 | 45 | 43.0 |
| gemma-3-4b-it | 0.3062 | 42 | 3.0382 | 40 | 41.0 |
| Qwen-Qwen2-VL-7B-Instruct | 0.3004 | 43 | 4.2122 | 25 | 34.0 |
| MediaTek-Research-Llama-Breeze2-3B-Instruct | 0.2971 | 44 | 2.8992 | 42 | 43.0 |
| MediaTek-Research-Llama-Breeze2-8B-Instruct | 0.2915 | 45 | 3.1374 | 38 | 41.5 |
| OpenGVLab-InternVL2-2B | 0.2891 | 46 | 2.2198 | 47 | 46.5 |
| phi-4-multimodal-instruct | 0.286 | 47 | 1.7863 | 50 | 48.5 |
| deepseek-ai-deepseek-vl2-tiny | 0.2781 | 48 | 2.0076 | 49 | 48.5 |
| THUDM-cogvlm2-llama3-chinese-chat-19B | 0.2777 | 49 | 2.9618 | 41 | 45.0 |
| OpenGVLab-InternVL2-1B | 0.2689 | 50 | 2.1298 | 48 | 49.0 |
| moonshotai-Kimi-VL-A3B-Instruct | 0.2 | 51 | 4.22 | 24 | 37.5 |
Models ordered by VisTW-MCQ Rank.
Citation
@article{tam2025vistw,
title={VisTW: Benchmarking Vision-Language Models for Traditional Chinese in Taiwan},
author={Tam, Zhi Rui and Pai, Ya-Ting and Lee, Yen-Wei and Chen, Yun-Nung},
journal={arXiv preprint arXiv:2503.10427},
year={2025}
}