SBBD

Paper Registration

1

Select Book

2

Select Paper

3

Fill in paper information

4

Congratulations

Fill in your paper information

English Information

(*) To change the order drag the item to the new position.

Authors
# Name
1 Lucas Costa(lucas.lage@dcc.ufmg.br)
2 Átila Souza(atilamelo@dcc.ufmg.br)
3 Marcelo Andrade(marcelo.migueletto@almg.gov.br)
4 Rodrygo Santos(rodrygo@dcc.ufmg.br)
5 Wagner Meira Jr.(meira@dcc.ufmg.br)
6 Gisele Pappa(glpappa@dcc.ufmg.br)

(*) To change the order drag the item to the new position.

Reference
# Reference
1 Brasil (2025). Regimento interno da Câmara dos Deputados. https://www2.camara.leg.br/atividade-legislativa/legislacao/regimento-interno-da-camara-dos-deputados. Accessed: 2026-05-01.
2 Brasil - Minas Gerais (2025). Regimento interno da Assembleia Legislativa do Estado de Minas Gerais. https://www.almg.gov.br/atividade-parlamentar/leis/legislacao-mineira/lei/texto/?tipo=RAL&num=5176&ano=1997&comp=&cons=1. Accessed: 2026-05-01.
3 Devlin, J., Chang, M., Lee, K., and Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In NAACL-HLT, pages 4171–4186. Association for Computational Linguistics.
4 Garcia, E., Silva, N., Siqueira, F., Gomes, J., Albuquerque, H. O., Souza, E., Lima, E., and de Carvalho, A. (2024). RoBERTaLexPT: A legal RoBERTa model pretrained with deduplication for Portuguese. In Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1, pages 374–383, Santiago de Compostela, Galicia/Spain. Association for Computational Lingustics.
5 Martins, M. and Medeiros, C. (2025). From anvisa leaflets to extended interoperability with global health databases: some pitfalls and success stories. In Anais do XIX Brazilian e-Science Workshop, pages 9–16, Porto Alegre, RS, Brasil. SBC.
6 Mistral AI (2025). Mistral-small-24b-instruct-2501. https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501. Accessed: 2026-05-01.
7 Navastara, D. A., Abdillah, S., Benito, D., Adillion, I. G., and Purwitasari, D. (2025). Document matching for contradiction detection in low-resource legislative texts with self-training and augmentation using transformer model. JANAPATI, 14(2):321–335.
8 OpenAI (2025a). Gpt-5 mini. https://developers.openai.com/api/docs/models/gpt-5-mini. Accessed: 2026-05-01.
9 OpenAI (2025b). Gpt-5 nano. https://developers.openai.com/api/docs/models/gpt-5-nano. Accessed: 2026-05-01.
10 Silva, M., Oliveira, G., Costa, L., and Pappa, G. (2024). Evaluating domain-adapted language models for governmental text classification tasks in Portuguese. In Anais do XXXIX SBBD, pages 247–259, Porto Alegre, RS, Brasil. SBC.
11 Silva, M. O., Oliveira, G. P., Costa, L. G. L., and Pappa, G. L. (2025). GovBERT-BR: A BERT-based language model for Brazilian Portuguese governmental data. In Intelligent Systems. BRACIS 2024, pages 19–32, Cham. Springer Nature Switzerland.
12 Souza, F., Nogueira, R., and Lotufo, R. (2020). BERTimbau: pretrained BERT models for Brazilian Portuguese. In 9th BRACIS, Rio Grande do Sul, Brazil, October 20-23.
13 Viegas, C. F. O., Costa, B. C., and Ishii, R. P. (2023). JurisBERT: A new approach that converts a classification corpus into an STS one. In Computational Science and Its Applications – ICCSA 2023, pages 349–365. Springer Nature Switzerland.
14 Zaiton, H., Alansary, S., Sarwat, N., and Hussein, I. (2026). Automatic detection of contradictions in legal texts: A computational linguistic approach. Procedia Computer Science, 275:503–512. 7th ACling.