Performance analysis of LLMs for abstractive summarization of brazilian legislative documents (2025)
- Authors:
- Autor USP: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC
- Unidade: ICMC
- DOI: 10.59490/dgo.2025.969
- Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL; APRENDIZADO COMPUTACIONAL; TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS; PORTUGUÊS DO BRASIL
- Keywords: large language models; summarization; legislative proposals
- Language: Inglês
- Imprenta:
- Publisher: Digital Government Society - DGS
- Publisher place: [S.l.]
- Date published: 2025
- Source:
- Título: Proceedings
- Conference titles: Annual International Conference on Digital Government Research - DG.O
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
LUCENA, Danilo Carlos Gouveia de et al. Performance analysis of LLMs for abstractive summarization of brazilian legislative documents. 2025, Anais.. [S.l.]: Digital Government Society - DGS, 2025. Disponível em: https://doi.org/10.59490/dgo.2025.969. Acesso em: 19 fev. 2026. -
APA
Lucena, D. C. G. de, Souza, E. P. R., Albuquerque, H. O., Silva, N. F. F. da, Oliveira, A. L. I. de, & Carvalho, A. C. P. de L. F. de. (2025). Performance analysis of LLMs for abstractive summarization of brazilian legislative documents. In Proceedings. [S.l.]: Digital Government Society - DGS. doi:10.59490/dgo.2025.969 -
NLM
Lucena DCG de, Souza EPR, Albuquerque HO, Silva NFF da, Oliveira ALI de, Carvalho ACP de LF de. Performance analysis of LLMs for abstractive summarization of brazilian legislative documents [Internet]. Proceedings. 2025 ;[citado 2026 fev. 19 ] Available from: https://doi.org/10.59490/dgo.2025.969 -
Vancouver
Lucena DCG de, Souza EPR, Albuquerque HO, Silva NFF da, Oliveira ALI de, Carvalho ACP de LF de. Performance analysis of LLMs for abstractive summarization of brazilian legislative documents [Internet]. Proceedings. 2025 ;[citado 2026 fev. 19 ] Available from: https://doi.org/10.59490/dgo.2025.969 - Gabinete pequeno é destaque de pc itautec
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Informações sobre o DOI: 10.59490/dgo.2025.969 (Fonte: oaDOI API)
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