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Related Questions
- What are some common challenges faced by zero-shot learning models in terms of data availability and quality?
- How do zero-shot learning models handle out-of-distribution data and what are the implications for their performance?
- Can you explain the difference between zero-shot learning and few-shot learning, and how do they relate to each other?
- What are some strategies for addressing the problem of overfitting in zero-shot learning models?
- How do zero-shot learning models handle concept drift, and what are the implications for their performance in real-world applications?
- Can you discuss the role of meta-learning in addressing the challenges of zero-shot learning?
- What are some potential applications of zero-shot learning in areas such as natural language processing and computer vision?
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