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Related Questions
- What are the key challenges of few-shot learning, and how does the cold start problem impact its performance?
- How can prompt engineering techniques, such as natural language processing and contextualization, help alleviate the cold start issue in few-shot learning?
- What are some effective strategies for designing high-quality prompts that enable few-shot learning models to generalize well to unseen tasks and domains?
- Can you explain the concept of 'prompt engineering' and its role in addressing the cold start problem in few-shot learning, with examples of successful applications?
- How does the quality of the input prompt affect the performance of few-shot learning models, and what are some best practices for crafting effective prompts?
- What are some common pitfalls or challenges associated with prompt engineering in few-shot learning, and how can they be addressed?
- Can you discuss the relationship between prompt engineering and transfer learning in the context of few-shot learning, and how they can be combined to improve model performance?
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