Near Feasibility Distant Practicality: Empirical Analysis of Deploying and Using LLMs on Resource-Constrained Smartphones
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Este artigo não possui um resumo.Referências
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Gottschalk, F. and Weise, C. (2023). Digital equity and inclusion in education: An overview of practice and policy in oecd countries.
Isotani, S., Bittencourt, I. I., Challco, G. C., Dermeval, D., and Mello, R. F. (2023). Aied unplugged: Leapfrogging the digital divide to reach the underserved. In International Conference on Artificial Intelligence in Education, pages 772–779. Springer.
Jeon, J. and Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and chatgpt. Education and Information Technologies, 28(12):15873–15892.
Monteiro Santos, M., Barros, A., Rodrigues, L., Dermeval, D., Primo, T., Ibert, I., and Isotani, S. (2025). Near feasibility, distant practicality: Empirical analysis of deploying and using llms on resource-constrained smartphones. In Proceedings of the 13th International Conference on Information & Communication Technologies and Development, ICTD ’24, page 224–235, New York, NY, USA. Association for Computing Machinery.
Rodrigues, L., Guerino, G., Silva, T. E., Challco, G. C., Oliveira, L., da Penha, R. S., Melo, R. F., Vieira, T., Marinho, M., Macario, V., et al. (2024a). Mathaide: A qualitative study of teachers’ perceptions of an its unplugged for underserved regions. International Journal of Artificial Intelligence in Education, pages 1–29.
Rodrigues, L., Pereira, F. D., Cabral, L., Gašević, D., Ramalho, G., and Mello, R. F. (2024b). Assessing the quality of automatic-generated short answers using gpt-4. Computers and Education: Artificial Intelligence, page 100248.
Veloso, T., Chalco Challco, G., Rogrigues, L., Versuti, F., Sena da Penha, R., Silva Oliveira, L., and Isotani, S. (2023). Its unplugged: Leapfrogging the digital divide for teaching numeracy skills in underserved populations. In Towards the Future of AI-augmented Human Tutoring in Math Learning 2023-Proceedings of the Workshop on International Conference of Artificial Intelligence in Education colocated with The 24th International Conference on Artificial Intelligence in Education.
Wang, B., Liu, J., Karimnazarov, J., and Thompson, N. (2024). Task supportive and personalized human-large language model interaction: A user study. In Proceedings of the 2024 Conference on Human Information Interaction and Retrieval, pages 370–375.
Crompton, H., Jones, M. V., and Burke, D. (2024). Affordances and challenges of artificial intelligence in k-12 education: A systematic review. Journal of Research on Technology in Education, 56(3):248–268.
Gottschalk, F. and Weise, C. (2023). Digital equity and inclusion in education: An overview of practice and policy in oecd countries.
Isotani, S., Bittencourt, I. I., Challco, G. C., Dermeval, D., and Mello, R. F. (2023). Aied unplugged: Leapfrogging the digital divide to reach the underserved. In International Conference on Artificial Intelligence in Education, pages 772–779. Springer.
Jeon, J. and Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and chatgpt. Education and Information Technologies, 28(12):15873–15892.
Monteiro Santos, M., Barros, A., Rodrigues, L., Dermeval, D., Primo, T., Ibert, I., and Isotani, S. (2025). Near feasibility, distant practicality: Empirical analysis of deploying and using llms on resource-constrained smartphones. In Proceedings of the 13th International Conference on Information & Communication Technologies and Development, ICTD ’24, page 224–235, New York, NY, USA. Association for Computing Machinery.
Rodrigues, L., Guerino, G., Silva, T. E., Challco, G. C., Oliveira, L., da Penha, R. S., Melo, R. F., Vieira, T., Marinho, M., Macario, V., et al. (2024a). Mathaide: A qualitative study of teachers’ perceptions of an its unplugged for underserved regions. International Journal of Artificial Intelligence in Education, pages 1–29.
Rodrigues, L., Pereira, F. D., Cabral, L., Gašević, D., Ramalho, G., and Mello, R. F. (2024b). Assessing the quality of automatic-generated short answers using gpt-4. Computers and Education: Artificial Intelligence, page 100248.
Veloso, T., Chalco Challco, G., Rogrigues, L., Versuti, F., Sena da Penha, R., Silva Oliveira, L., and Isotani, S. (2023). Its unplugged: Leapfrogging the digital divide for teaching numeracy skills in underserved populations. In Towards the Future of AI-augmented Human Tutoring in Math Learning 2023-Proceedings of the Workshop on International Conference of Artificial Intelligence in Education colocated with The 24th International Conference on Artificial Intelligence in Education.
Wang, B., Liu, J., Karimnazarov, J., and Thompson, N. (2024). Task supportive and personalized human-large language model interaction: A user study. In Proceedings of the 2024 Conference on Human Information Interaction and Retrieval, pages 370–375.
Publicado
24/11/2025
Como Citar
SANTOS, Mateus Monteiro; DERMEVAL, Diego; RODRIGUES, Luiz.
Near Feasibility Distant Practicality: Empirical Analysis of Deploying and Using LLMs on Resource-Constrained Smartphones. In: CONCURSO ALEXANDRE DIRENE (CTD-IE) - TRABALHOS DE CONCLUSÃO DE CURSO - CONGRESSO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (CBIE), 14. , 2025, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 117-118.
DOI: https://doi.org/10.5753/cbie_estendido.2025.13052.
