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Related Questions
- What are some common techniques used in prompt engineering to handle out-of-vocabulary words in medical text classification tasks?
- How can subword tokenization be used to address out-of-vocabulary words in medical text classification tasks?
- What is the role of context-dependent embedding in handling out-of-vocabulary words in medical text classification tasks?
- Can you explain how to use a combination of subword tokenization and context-dependent embedding to improve performance on out-of-vocabulary words in medical text classification tasks?
- How does prompt engineering address the issue of rare or novel medical terms in text classification tasks?
- What are some strategies for incorporating domain-specific knowledge into prompt engineering to improve handling of out-of-vocabulary words in medical text classification tasks?
- Can you discuss the trade-offs between using pre-trained language models and fine-tuning them for medical text classification tasks, particularly when dealing with out-of-vocabulary words?
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