pretty_name: MWS Vision Bench
dataset_name: mws-vision-bench
language:
- ru
license: cc-by-4.0
tags:
- benchmark
- multimodal
- ocr
- kie
- grounding
- vlm
- business
- russian
- document
- visual-question-answering
- document-question-answering
task_categories:
- visual-question-answering
- document-question-answering
size_categories:
- 1K<n<10K
annotations_creators:
- expert-generated
dataset_creators:
- MTS AI Research
papers:
- title: >-
MWS Vision Bench: The First Russian Business-OCR Benchmark for Multimodal
Models
authors:
- MTS AI Research Team
year: 2025
status: in preparation
note: Paper coming soon
homepage: https://huggingface.co/datasets/MTSAIR/MWS-Vision-Bench
repository: https://github.com/mts-ai/MWS-Vision-Bench
organization: MTSAIR
MWS-Vision-Bench
🇷🇺 Русскоязычное описание ниже / Russian summary below.
MWS Vision Bench — the first Russian-language business-OCR benchmark designed for multimodal large language models (MLLMs).
This is the validation split - publicly available for open evaluation and comparison.
🧩 Paper is coming soon.
🔗 Official repository: github.com/mts-ai/MWS-Vision-Bench
🏢 Organization: MTSAIR on Hugging Face
📰 Article on Habr (in Russian): “MWS Vision Bench — the first Russian business-OCR benchmark”
📊 Dataset Statistics
- Total samples: 1,302
- Unique images: 400
- Task types: 5
📁 Repository Structure
MWS-Vision-Bench/
├── metadata.jsonl # Dataset annotations
├── images/ # Image files organized by category
│ ├── business/
│ │ ├── scans/
│ │ ├── sheets/
│ │ ├── plans/
│ │ └── diagramms/
│ └── personal/
│ ├── hand_documents/
│ ├── hand_notebooks/
│ └── hand_misc/
└── README.md # This file
📋 Data Format
Each line in metadata.jsonl contains one JSON object:
{
"file_name": "images/image_0.jpg", # Path to the image
"id": "1", # Unique identifier
"type": "text grounding ru", # Task type
"dataset_name": "business", # Subdataset name
"question": "...", # Question in Russian
"answers": ["398", "65", ...] # List of valid answers (as strings)
}
🎯 Task Types
| Task | Description | Count |
|---|---|---|
document parsing ru |
Parsing structured documents | 243 |
full-page OCR ru |
End-to-end OCR on full pages | 144 |
key information extraction ru |
Extracting key fields | 119 |
reasoning VQA ru |
Visual reasoning in Russian | 400 |
text grounding ru |
Text–region alignment | 396 |
💻 Usage Example
from datasets import load_dataset
# Load dataset (authorization required if private)
dataset = load_dataset("MTSAIR/MWS-Vision-Bench", token="hf_...")
# Example iteration
for item in dataset:
print(f"ID: {item['id']}")
print(f"Type: {item['type']}")
print(f"Question: {item['question']}")
print(f"Image: {item['image_path']}")
print(f"Answers: {item['answers']}")
📄 License
MIT License
© 2024 MTS AI
See LICENSE for details.
📚 Citation
If you use this dataset in your research, please cite:
@misc{mwsvisionbench2024,
title={MWS-Vision-Bench: Russian Multimodal OCR Benchmark},
author={MTS AI Research},
organization={MTSAIR},
year={2025},
url={https://huggingface.co/datasets/MTSAIR/MWS-Vision-Bench},
note={Paper coming soon}
}
🤝 Contacts
- Team: MTSAIR Research
- Email: g.gaikov@mts.ai
🇷🇺 Краткое описание
MWS Vision Bench — первый русскоязычный бенчмарк для бизнес-OCR в эпоху мультимодальных моделей.
Он включает 1302 примера и 5 типов задач, отражающих реальные сценарии обработки бизнес-документов и рукописных данных.
Датасет создан для оценки и развития мультимодальных LLM в русскоязычном контексте.
📄 Научная статья в процессе подготовки (paper coming soon).
Made with ❤️ by MTS AI Research Team