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Related Questions
- What pre-training objectives are used by BERT and RoBERTa, and how do they differ?
- How do the masked language modeling and next sentence prediction objectives in BERT affect its ability to generalize to out-of-domain text?
- Do RoBERTa's changes to the BERT architecture, such as increasing the number of layers and epochs, improve its ability to generalize to out-of-domain text?
- How do the pre-training objectives of BERT and RoBERTa influence their ability to capture domain-specific knowledge and relationships?
- Can the pre-training objectives of BERT and RoBERTa be modified or fine-tuned to improve their ability to generalize to out-of-domain text?
- How do the pre-training objectives of BERT and RoBERTa affect their ability to handle out-of-vocabulary words and novel entities?
- What are some potential challenges or limitations of using the pre-training objectives of BERT and RoBERTa for out-of-domain text, and how can they be addressed?
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