If you have any questions, feel free to ask! :)
To ensure the correctness of the experimental results, please run QNN in FuxiCTR==2.0.1.
🔥Another version of QNN, which is based on user sequence modeling, is available at https://github.com/salmon1802/QIN.
🔥 KDD'25 accepted
Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction
python>=3.6
pytorch>=1.10
fuxictr==2.0.1
PyYAML
pandas
scikit-learn
numpy
h5py
tqdm
Get the datasets from https://github.com/reczoo/Datasets
Get the result from checkpoints
This implementation is based on FuxiCTR and BARS. Thanks for their sharing and contribution.
BARS: https://github.com/openbenchmark
FuxiCTR: https://github.com/xue-pai/FuxiCTR
If you find our code helpful for your research, please cite the following paper:
@article{li2025QNN,
title={Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction},
author={Li, Honghao and Zhang, Yiwen and Zhang, Yi and Sang, Lei and Zhu, Jieming},
journal={arXiv preprint arXiv:2505.17999},
year={2025}
}