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Authors
# Name
1 Alessandro Albuquerque(alex.marinho.natal@gmail.com)
2 Carina Dorneles(carina.dorneles@ufsc.br)
3 Igor Wensing(igormaywensing@gmail.com)
4 Nelson Filho(nelsonluizjoppifilho@gmail.com)

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Reference
# Reference
1 Finardi, P., Avila, L., Castaldoni, R., Gengo, P., Larcher, C., Piau, M., ... & Caridá, V. (2024). “The Chronicles of RAG: The Retriever, the Chunk and the Generator”. arXiv preprint arXiv:2401.07883. Rodrigues Cássio S, Cardoso, Geovane E., Ramos, Vinicius F. C. “Inteligência artificial no controle de sobrepreço em compras públicas”. Revista do Tribunal de Contas de Santa Catarina. Belo Horizonte. Ano 2. Número 2, p 225-252, nov. 2023/abr. 2024. Gao, M., Hu, X., Ruan, J., Pu, X., & Wan, X. (2024). “Llm-based nlg evaluation: Current status and challenges”. arXiv preprint arXiv:2402.01383.Dyer, S., Martin, J. and Zulauf, J. (1995) “Motion Capture White Paper”, http://reality.sgi.com/employees/jam_sb/mocap/MoCapWP_v2.0.html, December. Huang, H., Qu, Y., Liu, J., Yang, M., & Zhao, T. (2024). “An empirical study of llm-as-a-judge for llm evaluation: Fine-tuned judge models are task-specific classifiers”. arXiv preprint arXiv:2403.02839. OpenAI, “Moving AI governance forward”. Disponível em: https://openai.com/index/moving-ai-governance-forward/. Acesso em: 02/06/2024. Reddy, S., Rogers, W., Makinen, V. P., Coiera, E., Brown, P., Wenzel, M., ... & Kelly, B. (2021). “Evaluation framework to guide implementation of AI systems into healthcare settings”. BMJ health & care informatics, 28(1). Shankar, S., Zamfirescu-Pereira, J. D., Hartmann, B., Parameswaran, A. G., & Arawjo, I. (2024). “Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences”. arXiv preprint arXiv:2404.12272. Stahl, B. C., Antoniou, J., Bhalla, N., Brooks, L., Jansen, P., Lindqvist, B., ... & Wright, D. (2023). “A systematic review of artificial intelligence impact assessments”. Artificial Intelligence Review, 56(11), 12799-12831. Yu, H., Gan, A., Zhang, K., Tong, S., Liu, Q., & Liu, Z. (2024). “Evaluation of Retrieval-Augmented Generation: A Survey”. arXiv preprint arXiv:2405.07437.