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Related Questions
- How do contextualized word embeddings capture nuances in language, such as connotation and implication?
- Can you explain the impact of contextualized word embeddings on language models' ability to recognize idioms and figurative language?
- In what ways do contextualized word embeddings improve language models' performance in tasks that require understanding of subtle differences in word meanings?
- How do contextualized word embeddings address the limitations of traditional word embeddings in capturing complex linguistic relationships?
- Can you discuss the role of contextualized word embeddings in improving language models' ability to recognize sarcasm and other forms of subtle language?
- What are some potential challenges or limitations of using contextualized word embeddings in language models, and how can they be addressed?
- How do contextualized word embeddings compare to other techniques, such as attention mechanisms, in improving language models' performance on nuanced language tasks?
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