ELMRec (EMNLP'24)

Paper - [ArXiv]

• Enhancing High-order Interaction Awareness in LLM-based Recommender Model, EMNLP 2024 Main.
• Xinfeng Wang, Jin Cui, Fumiyo Fukumoto, and Yoshimi Suzuki.

Note

• The checkpoints of ELMRec were uploaded on Google Drive.
• If you have any questions, please feel free to contact me at kaysenn@163.com.

Train and test ELMRec

(1) Install requirements

    >> pip install -r requirements.txt

(2) Pretraining ({dataset}: beauty, sports, and toys.) (under ./ELMRec )

    >> python pretrain.py ./data/{dataset}/ --cuda --batch_size 64 --checkpoint ./checkpoint/{dataset}/

(3) Inference ({dataset}: beauty, sports, and toys.) (under ./ELMRec )

    >> python seq_reranker.py ./data/{dataset}/ --cuda --batch_size 16 --checkpoint ./checkpoint/{dataset}/
    >> python topn.py ./data/{dataset}/ --cuda --batch_size 16 --checkpoint ./checkpoint/{dataset}/
    >> python exp.py ./data/{dataset}/ --cuda --batch_size 16 --checkpoint ./checkpoint/{dataset}/

Parameters

Dataset	Direct Recommendation				Sequential Recommendation
	α	σ	N	L	α	σ	N	L
Sports	5	5	10	4	11	5	10	4
Beauty	9	6	15	4	6	6	15	4
Toys	9	5	10	4	5	5	10	4

Code Reference

• P5
• POD

Citation

If this repository helps you, please cite:

@article{wang2024enhancing,
  title={Enhancing High-order Interaction Awareness in LLM-based Recommender Model},
  author={Wang, Xinfeng and Cui, Jin and Fukumoto, Fumiyo and Suzuki, Yoshimi},
  journal={arXiv preprint arXiv:2409.19979},
  year={2024}
}