metadata

license: mit

BLaIR-roberta-base

BLaIR, which is short for "Bridging Language and Items for Retrieval and Recommendation", is a series of language models pre-trained on Amazon Reviews 2023 dataset.

BLaIR is grounded on pairs of (item metadata, language context), enabling the models to:

derive strong item text representations, for both recommendation and retrieval;
predict the most relevant item given simple / complex language context.

[📑 Paper] · [💻 Code] · [🌐 Amazon Reviews 2023 Dataset] · [🤗 Huggingface Datasets] · [🔬 McAuley Lab]

Model Details

Language(s) (NLP): English
License: MIT
Finetuned from model: roberta-base
Repository: https://github.com/hyp1231/AmazonReviews2023
Paper: https://arxiv.org/abs/2403.03952

Citation

If you find Amazon Reviews 2023 dataset, BLaIR checkpoints, Amazon-C4 dataset, or our scripts/code helpful, please cite the following paper.

@article{hou2024bridging,
  title={Bridging Language and Items for Retrieval and Recommendation},
  author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian},
  journal={arXiv preprint arXiv:2403.03952},
  year={2024}
}

Contact

Please let us know if you encounter a bug or have any suggestions/questions by filling an issue or emailing Yupeng Hou (@hyp1231) at [email protected].