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Related Questions
- How can active learning techniques help identify the most informative samples for LLMs to improve prompt performance?
- What are some common human-in-the-loop approaches used to improve LLM prompt performance, and how do they differ from each other?
- How can you use uncertainty sampling to select the most uncertain predictions from LLMs and have humans label them to improve prompt performance?
- What is the role of active learning in reducing the need for large amounts of labeled data for LLMs to achieve good performance?
- Can you describe a scenario where human-in-the-loop approaches are particularly effective in improving LLM prompt performance, and why?
- How can you use transfer learning to leverage knowledge from one task to improve LLM prompt performance on another task?
- What are some benefits and challenges of using active learning and human-in-the-loop approaches to improve LLM prompt performance, and how can they be addressed?
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