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Related Questions
- What strategies do LLMs employ to handle novel or unseen data during adaptation?
- How do LLMs distinguish between in-domain and out-of-domain data, and what are the consequences of misclassification?
- Can you explain the role of domain adaptation techniques in improving LLM performance on out-of-domain data?
- What are some common challenges LLMs face when adapting to new domains, and how can they be addressed?
- In what ways do LLMs leverage transfer learning to adapt to out-of-domain data, and what are the benefits of this approach?
- How do LLMs handle catastrophic forgetting when adapting to new domains, and what strategies can mitigate this issue?
- What are some state-of-the-art methods for adapting LLMs to out-of-domain data, and what are their key advantages and disadvantages?
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