- Attention Model
- Vaswani et al. “Attention Is All You Need”, NIPS 2017.
- SNEHA et al. , “An Attentive Survey of Attention Models“, ACM TIST, Jul 2021.
- XGBoost
- Tianqi Chen, Carlos Guestrin. XGBoost: A Scalable Tree Boosting System. University of Washington, Mar 2016.
- Deep Learning
- Liu, Z., Wang, Y., Vaidya, S., Ruehle, F., Halverson, J., Soljačić, M., Hou, T. Y., & Tegmark, M. (2024, April 30). KAN: Kolmogorov-Arnold Networks. arXiv.org. https://arxiv.org/abs/2404.19756
- Large Language Model (LLM)
- Wang, L., Yang, N., Huang, X., Yang, L., Majumder, R., & Wei, F. (2023). Improving text embeddings with large language models. arXiv preprint arXiv:2401.00368.
- Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., & Chen, W. (2021, June 17). LoRA: Low-Rank Adaptation of Large Language Models. arXiv.org. https://arxiv.org/abs/2106.09685
- Gloeckle, F., Idrissi, B. Y., Rozière, B., Lopez-Paz, D., & Synnaeve, G. (2024, April 30). Better & faster large language models via multi-Token prediction. arXiv.org. https://arxiv.org/abs/2404.19737
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