This is an official implementation of RE-SORT for CTR prediction task, as described in our paper:

RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction. arXiv preprint:2309.14891, 2024.

RE-SORT: A CTR prediction framework that removes spurious correlations in multilevel feature interactions, which leverages critical causal relationships between items and users in diverse nonlinear feature spaces to enhance the CTR prediction.

RE-SORT has the following dependencies:

• python 3.6+
• pytorch 1.10+

python run_expid.py --config {config_dir} --expid {experiment_id} --gpu {gpu_device_id}

If you find our RE-SORT helpful for your research, please consider citing the following paper:

@article{song2024resort,
  Title={RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction},
  journal={arXiv preprint:2309.14891},
  year={2024}
}