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Related Questions
- What are the key steps to design a data augmentation strategy for contrastive learning?
- How can you create analogous text passages through paraphrasing, back-translation, and data generation methods?
- What are some effective techniques to create non-analogous text passages using noise injection, adversarial attacks, and data corruption?
- What is the importance of balancing analogous and non-analogous text passages in contrastive learning?
- How can you evaluate the effectiveness of your data augmentation strategy in contrastive learning?
- What are the common challenges in designing a data augmentation strategy for contrastive learning, and how to overcome them?
- Can you provide an example of a data augmentation strategy for contrastive learning using a specific dataset and model?
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