This is the Pytorch implementation for our WSDM 2025 paper:

[WSDM 2025] Hongji Li, Hanwen Du, Youhua Li, Junchen Fu, Chunxiao Li, Ziyi Zhuang, Jiakang Li, Yongxin Ni (2025). Teach Me How to Denoise: A Universal Framework for Denoising Multi-modal Recommender Systems via Guided Calibration
WSDM '25: Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, Pages 782–791
https://doi.org/10.1145/3701551.3703507

1. Place the downloaded data (e.g. baby) into the data directory.
2. Enter the src folder and execute the following command:
   python main.py --teacher_model GUIDER --student_model BM3 -d baby

If you find Guider useful in your research, please consider citing our paper.

@inproceedings{li2025teach,
  title={Teach Me How to Denoise: A Universal Framework for Denoising Multi-modal Recommender Systems via Guided Calibration},
  author={Li, Hongji and Du, Hanwen and Li, Youhua and Fu, Junchen and Li, Chunxiao and Zhuang, Ziyi and Li, Jiakang and Ni, Yongxin},
  booktitle={Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining},
  pages={782--791},
  year={2025}
}

This code is made available solely for academic research purposes.

The structure of this code is inspired by the MMRec framework. We acknowledge and appreciate their valuable contributions.