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Related Questions
- What are the key components of a contrastive learning framework that can be applied to analogy recognition and generation?
- How can you design a data augmentation strategy to create pairs of analogous and non-analogous text passages for contrastive learning?
- What is the role of a similarity metric in contrastive learning for analogy recognition, and how can it be optimized?
- Can you explain the concept of 'negative sampling' in contrastive learning, and how it relates to analogy generation?
- How can you use contrastive learning to learn a representation space where analogies are preserved, and what are the benefits of this approach?
- What are some common challenges in applying contrastive learning to analogy recognition and generation, and how can they be addressed?
- Can you provide an example of a contrastive learning-based model architecture for analogy recognition and generation, and how it can be trained and evaluated?
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