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---
dataset_info:
- config_name: vision_bench_0701
features:
- name: question_id
dtype: string
- name: instruction
dtype: string
- name: image
dtype: image
- name: language
dtype: string
splits:
- name: test
num_bytes: 1654009592.0
num_examples: 500
download_size: 1653981819
dataset_size: 1654009592.0
- config_name: vision_bench_0617
features:
- name: question_id
dtype: string
- name: instruction
dtype: string
- name: image
dtype: image
- name: language
dtype: string
splits:
- name: test
num_bytes: 1193682526.0
num_examples: 500
download_size: 1193578497
dataset_size: 1193682526.0
configs:
- config_name: vision_bench_0701
data_files:
- split: test
path: vision_bench_0701/test-*
- config_name: vision_bench_0617
data_files:
- split: test
path: vision_bench_0617/test-*
---
# WildVision-Bench
We have two versions of Wildvision-Bench data
- `vision_bench_0617`: the selected 500 examples that best simulates the vision-arena elo ranking, same data in the paper.
- `vision_bench_0701`: the further filter and selected 500 examples by NSFW and manual selection. Leaderboard are still preparing.
## Evaluation
Please refer to our [Github](https://github.com/WildVision-AI/WildVision-Bench) for evaluation
If you want to evaluate your model, please use the `vision_bench_0617` version to fairly compare the performance with other models in the following leaderboard.
## Leaderboard (`vision_bench_0717`)
| Model | Score | 95% CI | Win Rate | Reward | Much Better | Better | Tie | Worse | Much Worse | Avg Tokens |
| :------------------------------: | :---: | :---------: | :------: | :----: | :---------: | :----: | :---: | :---: | :--------: | :--------: |
| gpt-4o | 89.15 | (-1.9, 1.5) | 80.6% | 56.4 | 255.0 | 148.0 | 14.0 | 72.0 | 11.0 | 142 |
| gpt-4-vision-preview | 79.78 | (-2.9, 2.2) | 71.8% | 39.4 | 182.0 | 177.0 | 22.0 | 91.0 | 28.0 | 138 |
| Reka-Flash | 64.65 | (-2.6, 2.7) | 58.8% | 18.9 | 135.0 | 159.0 | 28.0 | 116.0 | 62.0 | 168 |
| claude-3-opus-20240229 | 62.03 | (-3.7, 2.8) | 53.0% | 13.5 | 103.0 | 162.0 | 48.0 | 141.0 | 46.0 | 105 |
| yi-vl-plus | 55.05 | (-3.4, 2.3) | 52.8% | 7.2 | 98.0 | 166.0 | 29.0 | 124.0 | 83.0 | 140 |
| liuhaotian/llava-v1.6-34b | 51.89 | (-3.4, 3.8) | 49.2% | 2.5 | 90.0 | 156.0 | 26.0 | 145.0 | 83.0 | 153 |
| claude-3-sonnet-20240229 | 50.0 | (0.0, 0.0) | 0.2% | 0.1 | 0.0 | 1.0 | 499.0 | 0.0 | 0.0 | 114 |
| claude-3-haiku-20240307 | 37.83 | (-2.6, 2.8) | 30.6% | -16.5 | 54.0 | 99.0 | 47.0 | 228.0 | 72.0 | 89 |
| gemini-pro-vision | 35.57 | (-3.0, 3.2) | 32.6% | -21.0 | 80.0 | 83.0 | 27.0 | 167.0 | 143.0 | 68 |
| liuhaotian/llava-v1.6-vicuna-13b | 33.87 | (-2.9, 3.3) | 33.8% | -21.4 | 62.0 | 107.0 | 25.0 | 167.0 | 139.0 | 136 |
| deepseek-ai/deepseek-vl-7b-chat | 33.61 | (-3.3, 3.0) | 35.6% | -21.2 | 59.0 | 119.0 | 17.0 | 161.0 | 144.0 | 116 |
| THUDM/cogvlm-chat-hf | 32.01 | (-2.2, 3.0) | 30.6% | -26.4 | 75.0 | 78.0 | 15.0 | 172.0 | 160.0 | 61 |
| liuhaotian/llava-v1.6-vicuna-7b | 26.41 | (-3.3, 3.1) | 27.0% | -31.4 | 45.0 | 90.0 | 36.0 | 164.0 | 165.0 | 130 |
| idefics2-8b-chatty | 23.96 | (-2.2, 2.4) | 26.4% | -35.8 | 44.0 | 88.0 | 19.0 | 164.0 | 185.0 | 135 |
| Qwen/Qwen-VL-Chat | 18.08 | (-1.9, 2.2) | 19.6% | -47.9 | 42.0 | 56.0 | 15.0 | 155.0 | 232.0 | 69 |
| llava-1.5-7b-hf | 15.5 | (-2.4, 2.4) | 18.0% | -47.8 | 28.0 | 62.0 | 25.0 | 174.0 | 211.0 | 185 |
| liuhaotian/llava-v1.5-13b | 14.43 | (-1.7, 1.6) | 16.8% | -52.5 | 28.0 | 56.0 | 19.0 | 157.0 | 240.0 | 91 |
| BAAI/Bunny-v1_0-3B | 12.98 | (-2.0, 2.1) | 16.6% | -54.4 | 23.0 | 60.0 | 10.0 | 164.0 | 243.0 | 72 |
| openbmb/MiniCPM-V | 11.95 | (-2.4, 2.1) | 13.6% | -57.5 | 25.0 | 43.0 | 16.0 | 164.0 | 252.0 | 86 |
| bczhou/tiny-llava-v1-hf | 8.3 | (-1.6, 1.2) | 11.0% | -66.2 | 16.0 | 39.0 | 15.0 | 127.0 | 303.0 | 72 |
| unum-cloud/uform-gen2-qwen-500m | 7.81 | (-1.3, 1.7) | 10.8% | -68.5 | 16.0 | 38.0 | 11.0 | 115.0 | 320.0 | 92 |
## Citation
```
@article{lu2024wildvision,
title={WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences},
author={Lu, Yujie and Jiang, Dongfu and Chen, Wenhu and Wang, William Yang and Choi, Yejin and Lin, Bill Yuchen},
journal={arXiv preprint arXiv:2406.11069},
year={2024}
}
```
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