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Related Questions
- How does the number of attention heads affect the modeling of contextual relationships in machine translation?
- Can you explain the role of attention heads in enhancing the ability of the model to capture long-range dependencies?
- In what ways does the increased number of attention heads contribute to improved performance in sequence-to-sequence tasks like machine translation?
- What is the theoretical justification for using multiple attention heads in transformer models?
- How do the different attention heads communicate with each other to refine the representation of the input sequence?
- Can you discuss the implications of using a large number of attention heads on computational resources and model complexity?
- What techniques can be employed to regularize the attention heads in transformer models to prevent overfitting?
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