This is the official implementation of the following paper:
ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs [Paper]
Yuhan Li, Peisong Wang, Zhixun Li, Jeffrey Xu Yu, Jia Li
The framework of ZeroG.
Before you begin, ensure that you have Anaconda or Miniconda installed on your system. This guide assumes that you have a CUDA-enabled GPU. After create your conda environment (we recommend python==3.10), please run
pip install -r requirements.txt
to install python packages.
Datasets tech.pt and home.pt are availabel in this link, while other datasets in ZeroG are available in this link.
Please download and place them in folder datasets.
bash run.sh
📑 If you find our projects helpful to your research, please consider citing:
@article{li2024zerog,
title={ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs},
author={Li, Yuhan and Wang, Peisong and Li, Zhixun and Yu, Jeffrey Xu and Li, Jia},
journal={arXiv preprint arXiv:2402.11235},
year={2024}
}
🔥 A Survey of Graph Meets Large Language Model: Progress and Future Directions (IJCAI'24)
