Methods › Natural Language Processing › Contextualized Word Embeddings
Contextualized Word Embeddings
Self-Supervised Learning refers to a category of methods where we learn representations in a self-supervised way (i.e without labels). These methods generally involve a pretext task that is solved to learn a good representation and a loss function to learn with. Below you can find a continuously updating list of self-supervised methods.
Methods
All 5 methods in this collection, most-tagged first. Year is the archive's introduced_year; the archive stores 2000 when it has none, shown here as “–”. Papers counts distinct papers the archive tags with the method. Click a heading to sort.
| ELMo | – | 234 |
| USE Multilingual Universal Sentence Encoder | – | 26 |
| CoVe Contextual Word Vectors | – | 13 |
| Mirror-BERT | – | 6 |
| context2vec | – | 6 |