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English Information

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Authors
# Name
1 Livy Real(livyreal@icomp.ufam.edu.br)
2 Daniela Vianna(daniela.vianna@jusbrasil.com.br)
3 André Luiz Carvalho(andre@icomp.ufam.edu.br)
4 Altigran da Silva(alti@icomp.ufam.edu.br)

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Reference
# Reference
1 AISERA (2025). Llm evaluation: Key metrics, best practices and frameworks. https: //aisera.com/blog/llm-evaluation/. Accessed July 2025.
2 Dierk, C., Healey, J., and Dogan, D. (2025). Evaluating llms in experiential context. In Workshop on Human-centered Evaluation and Auditing of Language Models (HEAL), CHI 2025.
3 Gao, M., Hu, X., Ruan, J., Pu, X., and Wan, X. (2025). Llm-based nlg evaluation: Current status and challenges.
4 Jiao, J., Afroogh, S., Xu, Y., and Phillips, C. (2025). Navigating llm ethics: Advance- ments, challenges, and future directions.
5 Mathur, N., Baldwin, T., and Cohn, T. (2020). Tangled up in BLEU: Reevaluating the evaluation of automatic machine translation evaluation metrics. In Jurafsky, D., Chai, J., Schluter, N., and Tetreault, J., editors, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4984–4997, Online. Association for Computational Linguistics.
6 Meva, D. D. and Kukadiya, H. (2025). Performance evaluation of large language mod- els: A comprehensive review. International Research Journal of Computer Science, 12:109–114.
7 Minaee, S., Mikolov, T., Nikzad, N., Chenaghlu, M., Socher, R., Amatriain, X., and Gao, J. (2025). Large language models: A survey.
8 Peyrard, M. (2019). Studying summarization evaluation metrics in the appropriate scoring range. In Korhonen, A., Traum, D., and Ma`rquez, L., editors, Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5093–5100, Florence, Italy. Association for Computational Linguistics.