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Related Questions
- How do contextualized language models combine local and global information for word embedding generation?
- What are some common techniques used in contextualized language models for capturing sentence-level and document-level information?
- Can you explain the difference in word embedding generation between BERT and a non-contextualized word2vec model?
- How do contextualized models handle out-of-vocabulary words and word sense disambiguation?
- What is the role of attention mechanisms in contextualized language models?
- Can contextualized models be fine-tuned for specific downstream tasks, and how does this impact word embedding generation?
- What are some challenges and limitations of using contextualized language models for word embedding generation?
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