Name
Abstract | ||
|---|---|---|
In recent years, the Natural Language Processing community have been moving from uncontextualized word embeddings towards contextualized word embeddings. Among these contextualized architectures, BERT stands out due to its capacity to compute bidirectional contextualized word representations. However, its competitive performance in English downstream tasks is not obtained by its multilingual version when it is applied to other languages and domains. This is especially true in the case of the Spanish language used in Twitter. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.neucom.2020.09.078 | Neurocomputing |
Keywords | DocType | Volume |
Contextualized Embeddings,Spanish,Twitter,TWilBERT | Journal | 426 |
ISSN | Citations | PageRank |
0925-2312 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José-Ángel González | 1 | 0 | 1.69 |
| lluis f hurtado | 2 | 142 | 24.68 |
| Ferran Pla | 3 | 173 | 30.71 |