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Related Questions
- Can you provide examples of few-shot learning applications in natural language processing where prompt engineering played a crucial role?
- How do large language models leverage prompt engineering to improve their performance in few-shot learning settings?
- What are some common techniques used in prompt engineering for few-shot learning, and how do they impact model performance?
- Can you give examples of successful applications of prompt engineering in few-shot learning across different domains, such as text classification, question answering, and generation?
- How does the choice of prompt affect the performance of large language models in few-shot learning, and what are some best practices for prompt design?
- What are some challenges in applying prompt engineering in few-shot learning, and how can they be addressed?
- Can you discuss the relationship between prompt engineering and data efficiency in few-shot learning, and provide examples of how prompt engineering can improve data efficiency?
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