README.md

---
language:
- en
license: mit
task_categories:
- image-text-to-text
arxiv: 2505.20310
dataset_info:
  features:
  - name: field
    dtype: string
  - name: paper_idx
    dtype: string
  - name: doi
    dtype: string
  - name: type
    dtype: string
  - name: table_or_image
    dtype: image
  - name: text_or_caption
    dtype: string
  splits:
  - name: atmosphere
    num_bytes: 202134712.5
    num_examples: 1196
  - name: agriculture
    num_bytes: 446617002
    num_examples: 4336
  - name: environment
    num_bytes: 165016111.375
    num_examples: 1125
  download_size: 779035060
  dataset_size: 813767825.875
configs:
- config_name: default
  data_files:
  - split: atmosphere
    path: data/atmosphere-*
  - split: agriculture
    path: data/agriculture-*
  - split: environment
    path: data/environment-*
---

# Manalyzer: End-to-end Automated Meta-analysis with Multi-agent System

[**Project Page**](https://black-yt.github.io/meta-analysis-page/) | [**Paper**](https://huggingface.co/papers/2505.20310) | [**GitHub**](https://github.com/black-yt/Manalyzer)

## Overview

Meta-analysis is a systematic research methodology that synthesizes data from multiple existing studies to derive comprehensive conclusions. Traditional meta-analysis involves a complex multi-stage pipeline including literature retrieval, paper screening, and data extraction, which demands substantial human effort and time.

**Manalyzer** is a multi-agent system that achieves end-to-end automated meta-analysis through tool calls. This repository contains the benchmark constructed to evaluate meta-analysis performance, comprising 729 papers across 3 domains (Atmosphere, Agriculture, and Environment), encompassing text, image, and table modalities, with over 10,000 data points.

## Dataset Structure

The benchmark consists of 729 papers across 3 scientific domains:
- **Atmosphere**: 1,196 examples
- **Agriculture**: 4,336 examples
- **Environment**: 1,125 examples

### Data Fields

Each example in the dataset contains:
- `field`: The scientific domain (Atmosphere, Agriculture, or Environment).
- `paper_idx`: Unique index of the source paper.
- `doi`: Digital Object Identifier of the source paper.
- `type`: Category of the data point.
- `table_or_image`: Visual modality (extracted image of a table or figure).
- `text_or_caption`: Associated text or caption providing context for the visual content.

## Citation

If you find this dataset or the Manalyzer system useful in your research, please cite:

```bibtex
@article{xu2025manalyzer,
  title={Manalyzer: End-to-end Automated Meta-analysis with Multi-agent System},
  author={Xu, Wanghan and Zhang, Wenlong and Ling, Fenghua and Fei, Ben and Hu, Yusong and Ren, Fangxuan and Lin, Jintai and Ouyang, Wanli and Bai, Lei},
  journal={arXiv preprint arXiv:2505.20310},
  year={2025}
}
```