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Related Questions
- How does uncertainty estimation in active learning help improve the performance of large language models (LLMs)?
- What are the potential drawbacks of using uncertainty estimation in active learning for LLMs, and how can they be mitigated?
- Can you provide examples of uncertainty estimation methods used in active learning for LLMs, and their relative advantages and disadvantages?
- How does incorporating uncertainty estimation into the active learning process affect the interpretability of LLM outputs, and what are the implications for human evaluators?
- What is the relationship between uncertainty estimation and model calibration in the context of LLMs, and how do they impact each other?
- Can you describe the role of uncertainty estimation in active learning for LLMs in terms of reducing model overconfidence and improving generalizability?
- How can uncertainty estimation be used to identify and prioritize high-impact samples for active learning in LLMs?
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