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Related Questions
- What are the limitations of using data augmentation for improving LLMs in explanation generation?
- How does data augmentation compare to other methods such as prompt engineering in improving LLMs in explanation generation?
- What are the trade-offs between data augmentation and other methods such as transfer learning for improving LLMs in explanation generation?
- Can you explain the differences between data augmentation and other methods such as active learning in improving LLMs in explanation generation?
- What are the advantages and disadvantages of using data augmentation versus other methods such as feature augmentation for improving LLMs in explanation generation?
- How does data augmentation compare to other methods such as adversarial training in improving LLMs in explanation generation?
- What are the potential risks and challenges of relying solely on data augmentation for improving LLMs in explanation generation?
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