Gabriel Assis

According to our database, Gabriel Assis authored at least 8 papers between 2024 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Exploring Brazil's LLM Fauna: Investigating the Generative Performance of Large Language Models in Portuguese.

Gabriel Assis, Cláudia Freitas, Aline Paes

J. Braz. Comput. Soc., 2025

Meta4BR: Avaliando a Fidelidade Metafórica em Traduções de Metáforas para o Português por LLMs.

Luisa Stellet, Isabella Leite, Gabriel Assis, Aline Paes

Proceedings of the 16th Brazilian Symposium in Information and Human Language Technology, 2025

Diplomatrix-BR: Um Corpus Paralelo de Redações de Autoria Humana e de LLMs no Concurso de Diplomacia Brasileira.

Rodrigo Cavalcanti, Gabriela Casini, Gabriel Assis, Livy Real, Daniela Vianna, Paulo Mann, Aline Paes

Proceedings of the 16th Brazilian Symposium in Information and Human Language Technology, 2025

Language Flavors in the Lusophone World: A BERT-Based Social Media Study of Portuguese in Brazil, Portugal, and Mozambique.

Annie Amorim, Gabriel Assis, Laura Ribeiro, Daniel de Oliveira, Aline Paes

Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing, 2025

AIDAVANCE at the NTCIR-18 FinArg-2 Task: Making the Most ofSmall Language Models.

Hugo Dutra, Leonardo Martinho, Gabriel Assis, Jonnathan Carvalho, Aline Paes

Proceedings of the 18th NTCIR Conference on Evaluation of Information Access Technologies, 2025

2024

Explorando Técnicas de Aprendizado em Modelos de Linguagem para Classificação de Discurso de Ódio e Ofensivo em Português.

Gabriel Assis, Annie Amorim, Jonnathan Carvalho, Mariza Ferro, Daniel de Oliveira, Daniela Vianna, Aline Paes

Linguamática, 2024

Modestos e Sustentáveis: O Ajuste Eficiente Beneficia Modelos de Língua de Menor Escala em Português?

Gabriel Assis, Arthur B. Vasconcelos, Lívia de Azevedo, Mariza Ferro, Aline Paes

Proceedings of the 15th Brazilian Symposium in Information and Human Language Technology, 2024

Exploring Portuguese Hate Speech Detection in Low-Resource Settings: Lightly Tuning Encoder Models or In-Context Learning of Large Models?

Gabriel Assis, Annie Amorim, Jonnatahn Carvalho, Daniel de Oliveira, Daniela Q. C. Vianna, Aline Paes

Proceedings of the 16th International Conference on Computational Processing of Portuguese, 2024