How does contextual embedding work?

Can you explain how contextual embedding works in natural language processing?

Sure! Contextual embedding refers to the representation of words in a way that captures their meanings based on the surrounding context.

How is it different from traditional word embeddings?

Traditional word embeddings assign a fixed vector to each word, while contextual embeddings generate different vectors for the same word depending on its context.

Can you give me an example of contextual embedding in action?

Absolutely! In the sentence 'The bank can refuse to lend money,' the word 'bank' is understood differently than in 'I walked along the bank of the river.' Contextual embeddings capture these nuances.

What are some popular models that use contextual embeddings?

Popular models include BERT, ELMo, and GPT, which all utilize contextual embeddings to improve understanding of language.