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Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation
Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation (CIKM 2024)
Chengkai Liu, Jianghao Lin, Hanzhou Liu, Jianling Wang, James Caverlee
Paper: https://arxiv.org/abs/2406.12580
Usage
Requirements
- Python >= 3.7
- PyTorch >= 1.12
- CUDA >= 11.6
- Triton >= 2.2
- Install RecBole:
pip install recbole
- [optional] Install causal Conv1d with CUDA optimization for faster computation of Conv1D:
pip install causal-conv1d>=1.2.0
Run
python run.py
Please update config.yaml
to adjust the hyperparameters and experimental settings.
Citation
@inproceedings{liu2024behavior,
title={Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation},
author={Liu, Chengkai and Lin, Jianghao and Liu, Hanzhou and Wang, Jianling and Caverlee, James},
booktitle={Proceedings of the 33rd ACM International Conference on Information and Knowledge Management},
pages={1430--1440},
year={2024}
}
Acknowledgment
This project references RecBole, Accelerated Scan and Causal-Conv1d. We appreciate their outstanding work and commitment to open source.