Can contextual embeddings be used for translation?

Can contextual embeddings be used for translation?

Yes, contextual embeddings can significantly enhance translation quality by capturing the meaning of words in context.

How do contextual embeddings differ from traditional word embeddings?

Traditional word embeddings assign a fixed vector to each word, while contextual embeddings generate vectors based on surrounding words.

Can you give an example of how this works in practice?

Sure! In a sentence, the word 'bank' might have different embeddings depending on whether it's used in a financial context or a river context.

What are some popular models that use contextual embeddings?

Popular models include BERT, GPT, and ELMo, which all leverage contextual embeddings for various NLP tasks.