Source: Lecture Notes in Computer Science - LNCS. Conference titles: International Conference on Artificial Intelligence in Education - AIED. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, EDUCAÇÃO, LINGUAGEM
ABNT
BARROS, Aristoteles Peixoto et al. Evaluating large language model quality in resource-constrained environments: an educational stakeholders' survey on accuracy, completeness, and readability in Brazil. Lecture Notes in Computer Science - LNCS. Cham: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/978-3-031-98417-4_16. Acesso em: 19 abr. 2026. , 2026APA
Barros, A. P., Santos, M. M., Rodrigues, L. A. L., Dermeval, D., Isotani, S., & Pinto, I. I. B. S. (2026). Evaluating large language model quality in resource-constrained environments: an educational stakeholders' survey on accuracy, completeness, and readability in Brazil. Lecture Notes in Computer Science - LNCS. Cham: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.1007/978-3-031-98417-4_16NLM
Barros AP, Santos MM, Rodrigues LAL, Dermeval D, Isotani S, Pinto IIBS. Evaluating large language model quality in resource-constrained environments: an educational stakeholders' survey on accuracy, completeness, and readability in Brazil [Internet]. Lecture Notes in Computer Science - LNCS. 2026 ; 15878 218-232.[citado 2026 abr. 19 ] Available from: https://doi.org/10.1007/978-3-031-98417-4_16Vancouver
Barros AP, Santos MM, Rodrigues LAL, Dermeval D, Isotani S, Pinto IIBS. Evaluating large language model quality in resource-constrained environments: an educational stakeholders' survey on accuracy, completeness, and readability in Brazil [Internet]. Lecture Notes in Computer Science - LNCS. 2026 ; 15878 218-232.[citado 2026 abr. 19 ] Available from: https://doi.org/10.1007/978-3-031-98417-4_16


