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---
license: cc-by-4.0
configs:
- config_name: Element_Classification
data_files:
- split: test
path: Element_Classification/test-*
- config_name: Attribute_Regconition
data_files:
- split: test
path: Attribute_Regconition/test-*
- config_name: Visual_Grounding
data_files:
- split: test
path: Visual_Grounding/test-*
- config_name: OCR
data_files:
- split: test
path: OCR/test-*
- config_name: Code_Error_Correction
data_files:
- split: test
path: Code_Error_Correction/test-*
- config_name: Code_Function_Editing
data_files:
- split: test
path: Code_Function_Editing/test-*
- config_name: Webpage_HTML_Matching
data_files:
- split: test
path: Webpage_HTML_Matching/test-*
- config_name: Webpage_HTMl_Retrieval
data_files:
- split: test
path: Webpage_HTML_Retrieval/test-*
dataset_info:
- config_name: Element_Classification
features:
- name: id
dtype: string
- name: question
dtype: string
- name: image_id
dtype: string
- name: image
dtype: image
- name: answer
dtype: string
- name: subtask
dtype: string
splits:
- name: test
num_bytes: 442962174
num_examples: 950
download_size: 442962174
dataset_size: 442962174
- config_name: Attribute_Regconition
features:
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- name: question
dtype: string
- name: image_id
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num_examples: 3718
download_size: 1679258113
dataset_size: 1679258113
- config_name: Visual_Grounding
features:
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- name: question
dtype: string
- name: image_id
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dataset_size: 1897962456
- config_name: OCR
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- name: image_id
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dataset_size: 1147237990
- config_name: Code_Error_Correction
features:
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- name: question
dtype: string
- name: code_with_error
dtype: string
- name: answer
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- name: subtask
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- name: test
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dataset_size: 2885440
- config_name: Code_Function_Editing
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- name: question
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- name: function_description
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- name: answer
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- name: subtask
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splits:
- name: test
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num_examples: 2290
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dataset_size: 2712168
- config_name: Webpage_HTML_Matching
features:
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dtype: string
- name: question
dtype: string
- name: image_id
dtype: string
- name: image
dtype: image
- name: answer
dtype: string
- name: subtask
dtype: string
splits:
- name: test
num_bytes: 1003289265
num_examples: 2143
download_size: 1003289265
dataset_size: 1003289265
- config_name: Webpage_HTML_Retrieval
features:
- name: id
dtype: string
- name: question
dtype: string
- name: image_id
dtype: string
- name: image
dtype: image
- name: answer
dtype: string
- name: subtask
dtype: string
splits:
- name: test
num_bytes: 1109887493
num_examples: 2345
download_size: 1109887493
dataset_size: 1109887493
---
# WebUIBench
Dataset for the paper: [WebUIBench: A Comprehensive Benchmark for Evaluating Multimodal Large Language Models in WebUI-to-Code](https://arxiv.org/abs/2404.05955)
🏠 [Homepage](https://github.com/MAIL-Tele-AI/WebUIBench) | [**📖 arXiv**](https://arxiv.org/abs/2404.05955)
## Introduction
<!-- ![Task overview of WebUIBench from the WebUI Perception, HTML Programming, WebUI-HTML Understanding subtask and WebUI-to-Code task](https://github.com/MAIL-Tele-AI/WebUIBench/blob/main/imgs/overview.png) -->
We introduce WebUIBench, a large-scale and comprehensive benchmark designed to evaluate the WebUI-to-Code capabilities of Multimodal Large Language Models (MLLMs). WebUIBench comprises over **21K question-answer pairs** derived from more than **0.7K real-world websites**, encompassing **9 distinct subtasks**. We conducted extensive experiments on 7 state-of-the-art closed-source and 22 prominent open-source MLLMs. Our key findings highlight the models' deficiencies in webpage generation tasks across various dimensions, including cross-modality reasoning, element localization, and webpage layout generation.
## Contact
- Zhiyu Lin: [zyllin@bjtu.edu.cn](zyllin@bjtu.edu.cn)
- Zhengda Zhou: [zhengdazhou@smail.nju.edu.cn](zhengdazhou@smail.nju.edu.cn)
- Zhiyuan Zhao: [tuzixini@gmail.com](tuzixini@gmail.com)
# 🚩Citation
If you find this work is helpful, please kindly cite as follows. Thanks !
```bibtex
@article{webuibench,
title={WebUIBench: A Comprehensive Benchmark for Evaluating Multimodal Large Language Models in WebUI-to-Code},
author={Zhiyu Lin, Zhengda Zhou, Zhiyuan Zhao, Tianrui Wan, Yilun Ma, Junyu Gao, XueLong Li},
journal={arXiv preprint arXiv:xx},
year={2025}
}
```