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Related Questions
- How do BERT and RoBERTa's pre-training objectives, such as masked language modeling, influence their ability to understand figurative language?
- Can you explain how BERT and RoBERTa's contextualized word representations help them to disambiguate idioms and phrasal verbs?
- How do BERT and RoBERTa's architectures, including their self-attention mechanisms, enable them to capture the nuances of figurative language?
- What role do subword representations play in BERT and RoBERTa's ability to process idioms and phrasal verbs?
- How do BERT and RoBERTa's performance on figurative language tasks, such as idiomatic expression recognition, compare to other language models?
- Can you discuss the implications of BERT and RoBERTa's strengths and weaknesses in processing figurative language for natural language processing applications?
- How do BERT and RoBERTa's ability to handle figurative language impact their performance on downstream tasks, such as question answering and text classification?
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