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There is a growing interest in utilizing large-scale language models (LLMs) to advance next-generation Recommender Systems (RecSys), driven by their outstanding language understanding and in-context learning capabilities.
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2022
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2024
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H. Wang, S. Feng, T. He, Z. Tan, X. Han, and Y. Tsvetkov, “Can language models solve graph problems in natural language?” Advances in Neural Information Processing Systems , vol. 36, 2024
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2024
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N. F. Liu, K. Lin, J. Hewitt, A. Paranjape, M. Bevilacqua, F. Petroni, and P. Liang, “Lost in the middle: How language models use long contexts,” Transactions of the Association for Computational Linguistics , vol. 12, pp. 157–173, 2024
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J. Li, Y. Liu, W. Fan, X.-Y. Wei, H. Liu, J. Tang, and Q. Li, “Empowering molecule discovery for molecule-caption translation with large language models: A chatgpt perspective,” IEEE Transactions on Knowledge and Data Engineering , 2024
2024
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