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Related Questions
- What are the key differences between prompt optimization techniques like knowledge distillation and data augmentation in multi-task learning models?
- How does the choice of prompt optimization technique impact the transfer learning capabilities of a model trained on multiple tasks?
- Can you explain the role of prompt engineering in improving the transfer learning capabilities of multi-task learning models?
- What are some common challenges associated with transfer learning in multi-task learning models, and how can prompt optimization techniques help address them?
- How does the type of prompt optimization technique used affect the model's ability to generalize to new tasks?
- What is the relationship between prompt optimization techniques and the concept of 'task similarity' in multi-task learning?
- Can you discuss the trade-offs between using different prompt optimization techniques in multi-task learning models, such as between accuracy and interpretability?
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