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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)!