Exploring a POS-based two-stage approach for improving low-resource AMR-to-text generation (2022)
- Authors:
- USP affiliated authors: PARDO, THIAGO ALEXANDRE SALGUEIRO - ICMC ; CABEZUDO, MARCO ANTONIO SOBREVILLA - ICMC
- Unidade: ICMC
- Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL; TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS; PORTUGUÊS DO BRASIL
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: ACL
- Publisher place: Stroudsburg
- Date published: 2022
- Source:
- Título do periódico: Proceedings
- Conference titles: Workshop on Natural Language Generation, Evaluation, and Metrics - GEM
-
ABNT
CABEZUDO, Marco Antonio Sobrevilla e PARDO, Thiago Alexandre Salgueiro. Exploring a POS-based two-stage approach for improving low-resource AMR-to-text generation. 2022, Anais.. Stroudsburg: ACL, 2022. Disponível em: https://aclanthology.org/2022.gem-1.49. Acesso em: 19 abr. 2024. -
APA
Cabezudo, M. A. S., & Pardo, T. A. S. (2022). Exploring a POS-based two-stage approach for improving low-resource AMR-to-text generation. In Proceedings. Stroudsburg: ACL. Recuperado de https://aclanthology.org/2022.gem-1.49 -
NLM
Cabezudo MAS, Pardo TAS. Exploring a POS-based two-stage approach for improving low-resource AMR-to-text generation [Internet]. Proceedings. 2022 ;[citado 2024 abr. 19 ] Available from: https://aclanthology.org/2022.gem-1.49 -
Vancouver
Cabezudo MAS, Pardo TAS. Exploring a POS-based two-stage approach for improving low-resource AMR-to-text generation [Internet]. Proceedings. 2022 ;[citado 2024 abr. 19 ] Available from: https://aclanthology.org/2022.gem-1.49 - NILC at SR'20: exploring pre-trained models in surface realisation
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- The AMR-PT corpus and the semantic annotation of challenging sentences from journalistic and opinion texts
- Investigação de métodos de desambiguação lexical de sentidos de verbos do português do Brasil
- Geração de linguagem natural por meio de representações semânticas abstratas para o português do Brasil
- Public riots in Twitter: domain-based event filtering during civil unrest
- Efficient strategies for hierarchical text classification: external knowledge and auxiliary tasks
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