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Rede Neural Gráfica Multilíngue×Embeddings de Sentenças Multilíngues×
ÁreaAprendizado profundoAprendizado profundo
FamíliaMachine learningMachine learning
Ano de origem20192019–2022
Autor originalVarious (Kipf & Welling 2017 for GNN; multilingual extensions from NLP community ~2019)Reimers, N. & Gurevych, I.; Feng, F. et al. (Google)
TipoGraph-based deep learning with multilingual node/edge featuresCross-lingual representation learning
Fonte seminalKipf, T. N., & Welling, M. (2017). Semi-supervised classification with graph convolutional networks. In Proceedings of ICLR 2017. link ↗Reimers, N. & Gurevych, I. (2020). Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation. Proceedings of EMNLP 2020, 4512–4525. link ↗
Outros nomesMultilingual GNN, cross-lingual GNN, multilingual graph network, multilingual relational GNNmultilingual sentence representations, cross-lingual sentence embeddings, mSE, multilingual semantic embeddings
Relacionados55
ResumoA Multilingual Graph Neural Network (Multilingual GNN) applies graph-based message-passing over nodes and edges that carry features from two or more languages. It is used for tasks such as cross-lingual entity alignment, multilingual knowledge-graph completion, and relation extraction across parallel or comparable corpora, allowing structural and semantic information from multiple languages to be jointly learned.Multilingual sentence embeddings map sentences from many languages into a single shared vector space so that semantically equivalent sentences — regardless of language — land close together. Models such as LaBSE, multilingual Sentence-BERT, and mUSE have made it practical to compare, retrieve, and classify text across 50 to 100+ languages without translating anything first.
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ScholarGateComparar métodos: Multilingual graph neural network · Multilingual Sentence Embeddings. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare