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Related Questions
- What is contextualized embedding and how does it differ from traditional word embeddings?
- How does contextualized embedding help to capture nuances of language and reduce ambiguity?
- Can you provide examples of how contextualized embedding can improve the accuracy of language models?
- How does contextualized embedding address the issue of out-of-vocabulary words?
- What are some common applications of contextualized embedding in natural language processing?
- How does contextualized embedding help to reduce bias in language models by capturing context-dependent relationships?
- Can you explain the difference between contextualized embedding and other techniques for reducing bias in language models, such as debiasing word embeddings?
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