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Related Questions
- Can fine-tuning on specific datasets improve the handling of domain-specific out-of-vocabulary words?
- How does the size and diversity of the pre-training dataset impact the ability to handle out-of-vocabulary words?
- Do BERT and RoBERTa models have pre-trained representations for out-of-vocabulary words, and if so, how?
- Can language model fine-tuning using masked language modeling tasks reduce the impact of out-of-vocabulary words?
- How does the use of subword segmentation in BERT and RoBERTa affect the ability to handle out-of-vocabulary words?
- Can the addition of external knowledge graphs or specialized datasets improve the handling of out-of-vocabulary words?
- To what extent do BERT and RoBERTa's pre-trained representations generalize across different domains and tasks in handling out-of-vocabulary words?
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