Augmenting Paraphrase Generation with Syntax Information Using Graph Convolutional Networks

Paraphrase generation is an important yet challenging task in natural language processing. Neural network-based approaches have achieved remarkable success in sequence-to-sequence learning. Previous paraphrase generation work generally ignores syntactic information regardless of its availability, wi...

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Detalles Bibliográficos
Autores principales: Chi, Xiaoqiang, Xiang, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147394/
https://www.ncbi.nlm.nih.gov/pubmed/34063312
http://dx.doi.org/10.3390/e23050566

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147394/
https://www.ncbi.nlm.nih.gov/pubmed/34063312
http://dx.doi.org/10.3390/e23050566

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