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Related Questions
- Can you explain the role of prompt engineering in fine-tuning large language models for specific domains?
- How does incorporating external knowledge into prompts improve the performance of large language models?
- In what ways can multi-source feedback be used to improve the accuracy and relevance of large language model outputs in specific domains?
- What are some best practices for designing effective prompts that leverage external knowledge and multi-source feedback to enhance large language model performance?
- Can you discuss the challenges of incorporating external knowledge and multi-source feedback in prompt engineering, and provide examples of how to address them?
- In what ways can prompt engineering be used to adapt large language models to new or emerging domains, and how can external knowledge and multi-source feedback be used to support this process?
- How can the design of prompts be optimized for specific tasks and domains using techniques such as active learning and transfer learning?
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