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Related Questions
- How can I use subwordization to improve BERT's ability to handle low-frequency words?
- What are some techniques to augment RoBERTa's training data with synthetic data to reduce the impact of low-frequency words?
- Can I use data augmentation techniques such as back-translation or round-trip translation to improve the representation of low-frequency words in BERT and RoBERTa?
- How can I incorporate domain-specific knowledge into BERT and RoBERTa's training data to reduce the impact of low-frequency words?
- What are some methods to use transfer learning to adapt BERT and RoBERTa to specific domains with low-frequency words?
- Can I use data augmentation techniques such as paraphrasing or semantic role labeling to improve the representation of low-frequency words in BERT and RoBERTa?
- How can I use multi-task learning to reduce the impact of low-frequency words in BERT and RoBERTa by training on multiple related tasks?
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