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Large language models (LLMs) such as ChatGPT have gained considerable interest across diverse research communities.
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T. Chen, T. He, M. Benesty, V. Khotilovich, Y. Tang, H. Cho, K. Chen, R. Mitchell, I. Cano, T. Zhou et al. , “Xgboost: extreme gradient boosting,” R package version 0.4-2 , vol. 1, no. 4, pp. 1–4, 2015
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T. Sterling and J. J. Irwin, “Zinc 15–ligand discovery for everyone,” Journal of Chemical Information and Modeling , vol. 55, no. 11, pp. 2324–2337, 2015
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G. Biau and E. Scornet, “A random forest guided tour,” TEST , vol. 25, pp. 197–227, 2016
2016
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2018
Cited alongside, same era.
2018
Cited alongside, same era.
R. Luo, L. Sun, Y. Xia, T. Qin, S. Zhang, H. Poon, and T.-Y. Liu, “Biogpt: generative pre-trained transformer for biomedical text generation and mining,” Briefings in Bioinformatics , vol. 23, no. 6, Sep. 2022. [Online]. Available: http://dx.doi.org/10.1093/bib/bbac409
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