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license: cc-by-nc-4.0 |
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language: |
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- en |
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--- |
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# RecGPT: Generative Pre-training for Text-based Recommendation |
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We present the first domain-adapted and fully-trained large language model, RecGPT-7B, and its instruction-following variant, RecGPT-7B-Instruct, for text-based recommendation. Experimental results on rating prediction and sequential recommendation tasks show that our model, RecGPT-7B-Instruct, outperforms previous strong baselines. The general architecture and experimental results of RecGPT can be found in our [paper](arxivlink): |
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``` |
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@inproceedings{RecGPT, |
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title = {{RecGPT: Generative Pre-training for Text-based Recommendation}}, |
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author = {Hoang Ngo and Dat Quoc Nguyen}, |
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booktitle = {Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics}, |
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year = {2024} |
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} |
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``` |
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We publicly release the RecGPT models along with their pre-training and fine-tuning datasets. |
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Please cite our paper whenever RecGPT or the datasets are used to help produce published results or are incorporated into other software. |
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For further information or requests, please go to [RecGPT's homepage](https://github.com/VinAIResearch/RecGPT)! |
