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Related Questions
- What are the key differences between the transformer and BERT architectures in terms of explanation generation?
- How do self-attention mechanisms in transformer models contribute to explanation generation?
- What role does contextualized word representations play in BERT's ability to generate explanations?
- Can you explain how pre-training and fine-tuning impact the generation of explanations in transformer-based models?
- What are some common challenges in generating explanations for transformer and BERT models, and how can they be addressed?
- How do transformer and BERT models handle out-of-vocabulary words and their impact on explanation generation?
- Can you discuss the relationship between model interpretability and explanation generation in transformer and BERT models?
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