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Mamba4Rec

Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models (RelKD@KDD 2024 Best Paper Award Award)
Chengkai Liu, Jianghao Lin, Jianling Wang, Hanzhou Liu, James Caverlee
Paper: https://arxiv.org/abs/2403.03900

Usage

Requirements

• Python 3.7+
• PyTorch 1.12+
• CUDA 11.6+
• Install RecBole:
  • pip install recbole
• Install causal Conv1d and the core Mamba package:
  • pip install causal-conv1d>=1.2.0
  • pip install mamba-ssm

You can also refer to the required environment specifications in environment.yaml.

Run

python run.py

Specifying the dataset in config.yaml will trigger an automatic download. Please set an appropriate maximum sequence length in config.yaml for each dataset before training.

Citation

@article{liu2024mamba4rec,
  title={Mamba4rec: Towards efficient sequential recommendation with selective state space models},
  author={Liu, Chengkai and Lin, Jianghao and Wang, Jianling and Liu, Hanzhou and Caverlee, James},
  journal={arXiv preprint arXiv:2403.03900},
  year={2024}
}

Acknowledgment

This project is based on Mamba, Causal-Conv1d, and RecBole. Thanks for their excellent works.