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English Information

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Authors
# Name
1 Samuel Henrique Santos Silva(shss@ecomp.poli.br)
2 Allan Miller Silva Lima(amsl@ecomp.poli.br)
3 Denis Mayr Lima Martins(martins.denis@usp.br)
4 Fernando Buarque de Lima Neto(fbln@ecomp.poli.br)

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Reference
# Reference
1 Arora, S., Narayan, A., Chen, M. F., Orr, L., Guha, N., Bhatia, K., Chami, I., and Re, C. (2023). Ask me anything: A simple strategy for prompting language models. In The Eleventh International Conference on Learning Representations.
2 Han, Z., Gao, C., Liu, J., Zhang, J., and Zhang, S. Q. (2024). Parameter-efficient fine-tuning for large models: A comprehensive survey. 3.
3 Hu, T. and Zhou, X.-H. (2024). Unveiling llm evaluation focused on metrics: Challenges and solutions.
4 Huijben, I. A., Nijdam, A. A., Overeem, S., Van Gilst, M. M., and Van Sloun, R. (2023). Som-cpc: Unsupervised contrastive learning with self-organizing maps for structured representations of high-rate time series. In International Conference on Machine Learning, pages 14132–14152. PMLR.
5 Kohonen, T. (1990). The self-organizing map. Proceedings of the IEEE, 78(9):1464–1480.
6 Li, W., Wang, X., Li, W., and Jin, B. (2025). A survey of automatic prompt engineering: An optimization perspective.
7 Manduchi, L., Hüser, M., Vogt, J. E., Rätsch, G., and Horn, M. (2019). Deep probabilistic clustering with self-organizing maps. arXiv preprint arXiv:1910.01590.
8 Mao, W., Wu, J., Chen, W., Gao, C., Wang, X., and He, X. (2025). Reinforced prompt personalization for recommendation with large language models. ACM Trans. Inf. Syst., 43(3).
9 Papineni, K., Roukos, S., Ward, T., and Zhu, W.-J. (2002). Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, ACL '02, page 311–318, USA. Association for Computational Linguistics.
10 Wang, W., Wei, F., Dong, L., Bao, H., Yang, N., and Zhou, M. (2020). Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers. Advances in neural information processing systems, 33:5776–5788. 12.
11 Yang, A., Li, A., Yang, B., Zhang, B., Hui, B., Zheng, B., Yu, B., Gao, C., Huang, C., Lv, C., et al. (2025). Qwen3 technical report. arXiv preprint arXiv:2505.09388.
12 Yazan, M., Verberne, S., and Situmeang, F. (2025). Improving rag for personalization with author features and contrastive examples. In European Conference on Information Retrieval, pages 408–416. Springer.
13 Zhang, X., Zhao, J., and LeCun, Y. (2015). Character-level convolutional networks for text classification. In Cortes, C., Lawrence, N., Lee, D., Sugiyama, M., and Garnett, R., editors, Advances in Neural Information Processing Systems, volume 28. Curran Associates, Inc.