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Related Questions
- What are some common techniques used by LLMs to detect and handle out-of-distribution data?
- How do LLMs determine when to be cautious when encountering ambiguous or uncertain data?
- Can you explain the concept of 'calibration' in the context of LLMs and out-of-distribution data?
- What are some strategies for LLMs to mitigate the effects of uncertainty when dealing with novel or unseen data?
- How do LLMs handle the trade-off between accuracy and interpretability when encountering ambiguous data?
- What is the role of knowledge graph-based methods in helping LLMs navigate uncertainty and ambiguity?
- Can you discuss the importance of data augmentation techniques in reducing the impact of out-of-distribution data on LLMs?
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