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Related Questions
- What are the key benefits of combining knowledge distillation with data augmentation in LLMs?
- How can ensemble methods be used to combine the predictions of multiple knowledge distilled models?
- What are some common challenges that arise when combining knowledge distillation with other techniques in LLMs?
- Can you explain the concept of 'teacher-student' architecture in knowledge distillation and how it relates to LLMs?
- How does the choice of distillation loss function affect the performance of knowledge distillation in LLMs?
- What are some techniques for selecting the optimal hyperparameters for knowledge distillation in LLMs?
- How can knowledge distillation be used to improve the robustness of LLMs to adversarial attacks?
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