README.md

metadata

license: cc-by-4.0
task_categories:
  - graph-ml
tags:
  - multimodal
  - attributed-graph
  - benchmark

MAGB

This repository contains the Multimodal Attribute Graph Benchmark (MAGB) datasets described in the paper When Graph meets Multimodal: Benchmarking on Multimodal Attributed Graphs Learning.

Github repository

MAGB provides 5 datasets from E-Commerce and Social Networks, and evaluates two major learning paradigms: GNN-as-Predictor and VLM-as-Predictor. The datasets are publicly available on Hugging Face: https://huggingface.co/datasets/Sherirto/MAGB.

Each dataset consists of several parts:

• Graph Data (*.pt): Stores the graph structure, including adjacency information and node labels. Loadable using DGL.
• Node Textual Metadata (*.csv): Contains node textual descriptions, neighborhood relationships, and category labels.
• Text, Image, and Multimodal Features (TextFeature/, ImageFeature/, MMFeature/): Pre-extracted embeddings from the MAGB paper for different modalities.
• Raw Images (*.tar.gz): A compressed folder containing images named by node IDs. Requires extraction before use. The Reddit-M dataset is particularly large and may require special handling (see Github README for details).

📖 Table of Contents

• 📖 Introduction
• 💻 Installation
• 🚀 Usage
• 📊 Results
• 🤝 Contributing
• ❓ FAQ

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📖 Introduction

Multimodal attributed graphs (MAGs) incorporate multiple data types (e.g., text, images, numerical features) into graph structures, enabling more powerful learning and inference capabilities.
This benchmark provides:
✅ Standardized datasets with multimodal attributes.
✅ Feature extraction pipelines for different modalities.
✅ Evaluation metrics to compare different models.
✅ Baselines and benchmarks to accelerate research.

---

💻 Installation

Ensure you have the required dependencies installed before running the benchmark.

# Clone the repository
git clone https://github.com/sktsherlock/MAGB.git
cd MAGB

# Install dependencies
pip install -r requirements.txt

🚀 Usage

1. Download the datasets from MAGB. 👐

cd Data/
sudo apt-get update && sudo apt-get install git-lfs && git clone https://huggingface.co/datasets/Sherirto/MAGB .
ls

Now, you can see the Movies, Toys, Grocery, Reddit-S and Reddit-M under the ''Data'' folder.

2. GNN-as-Predictor

...(rest of the content from Github README can be pasted here)