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Related Questions
- What are the limitations of using word embeddings trained on general-purpose datasets for domain-specific tasks?
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- Can you explain the concept of contextualized word embeddings and their applications in natural language processing?
- What is the impact of using subword-based models on the performance of deep learning models for language understanding?
- How do you evaluate the quality of pre-trained language models for specific downstream tasks, and what metrics are typically used?
- What are the trade-offs between using rule-based and machine learning-based approaches for handling out-of-vocabulary words in deep learning models?
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