CoVe

2000년 도입 · 논문 13편에서 사용

CoVe, or Contextualized Word Vectors, uses a deep 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.

출처: Learned in Translation: Contextualized Word Vectors

소개 논문: Learned in Translation: Contextualized Word Vectors