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Related Questions
- What is the key difference between contextualized and static word embeddings?
- Can you provide an example of how contextualized word embeddings capture nuances of word meanings?
- How do contextualized word embeddings address the limitations of static word embeddings in capturing polysemy and homographs?
- What is the impact of contextualized word embeddings on downstream NLP tasks such as sentiment analysis and question answering?
- Can you explain the role of attention mechanisms in contextualized word embeddings?
- How do contextualized word embeddings compare to static word embeddings in terms of their ability to capture word relationships and analogies?
- What are some common applications of contextualized word embeddings in natural language processing?
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