CoVe
Contextual Word Vectors
**CoVe**, or **Contextualized Word Vectors**, uses a deep [LSTM](https://paperswithcode.com/method/lstm) encoder from an attentional sequence-to-sequence model trained for machine translation to contextualize word vectors. $\text{CoVe}$ word embeddings are therefore a function of the entire input sequence. These word embeddings can then be used in downstream tasks by concatenating them with $\text{GloVe}$ embeddings:

$$ v = \left[\text{GloVe}\left(x\right), \text{CoVe}\left(x\right)\right]$$

and then feeding these in as features for the task-specific models.
Learned in Translation: Contextualized Word Vectors
https://paperswithcode.com/paper/learned-in-translation-contextualized-word
Learned in Translation: Contextualized Word Vectors