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--- |
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license: mit |
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datasets: |
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- McAuley-Lab/Amazon-Reviews-2023 |
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language: |
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- en |
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tags: |
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- recommendation |
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- information retrieval |
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- Amazon Reviews 2023 |
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--- |
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# BLaIR-roberta-base |
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<!-- Provide a quick summary of what the model is/does. --> |
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BLaIR, which is short for "**B**ridging **La**nguage and **I**tems for **R**etrieval and **R**ecommendation", is a series of language models pre-trained on Amazon Reviews 2023 dataset. |
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BLaIR is grounded on pairs of *(item metadata, language context)*, enabling the models to: |
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* derive strong item text representations, for both recommendation and retrieval; |
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* predict the most relevant item given simple / complex language context. |
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[[馃搼 Paper](https://arxiv.org/abs/2403.03952)] 路 [[馃捇 Code](https://github.com/hyp1231/AmazonReviews2023)] 路 [[馃寪 Amazon Reviews 2023 Dataset](https://amazon-reviews-2023.github.io/)] 路 [[馃 Huggingface Datasets](https://huggingface.co/datasets/McAuley-Lab/Amazon-Reviews-2023)] 路 [[馃敩 McAuley Lab](https://cseweb.ucsd.edu/~jmcauley/)] |
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## Model Details |
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- **Language(s) (NLP):** English |
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- **License:** MIT |
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- **Finetuned from model:** [roberta-base](https://huggingface.co/FacebookAI/roberta-base) |
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- **Repository:** [https://github.com/hyp1231/AmazonReviews2023](https://github.com/hyp1231/AmazonReviews2023) |
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- **Paper:** [https://arxiv.org/abs/2403.03952](https://arxiv.org/abs/2403.03952) |
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## Citation |
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If you find Amazon Reviews 2023 dataset, BLaIR checkpoints, Amazon-C4 dataset, or our scripts/code helpful, please cite the following paper. |
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```bibtex |
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@article{hou2024bridging, |
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title={Bridging Language and Items for Retrieval and Recommendation}, |
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author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian}, |
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journal={arXiv preprint arXiv:2403.03952}, |
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year={2024} |
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} |
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``` |
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## Contact |
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Please let us know if you encounter a bug or have any suggestions/questions by [filling an issue](https://github.com/hyp1231/AmazonReview2023/issues/new) or emailing Yupeng Hou ([@hyp1231](https://github.com/hyp1231)) at [[email protected]](mailto:[email protected]). |