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Related Questions
- What are some common data augmentation techniques used in natural language processing?
- How can we apply data augmentation to improve the robustness of a language model on a new task?
- What are some potential risks and challenges associated with using data augmentation techniques?
- Can you provide examples of how data augmentation can be used to improve language model performance on tasks such as sentiment analysis or question answering?
- How can we evaluate the effectiveness of data augmentation techniques on a new task?
- What are some techniques for generating high-quality augmented data, such as paraphrasing or back-translation?
- How can we balance the trade-off between data augmentation and overfitting on a new task?
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