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Related Questions
- What are some common issues with adapting large language models to new domains, and how can domain adaptation help address them?
- What are the key differences between domain adaptation and few-shot learning in the context of LLMs, and how do they intersect?
- How can we leverage few-shot learning to adapt LLMs to new domains with limited labeled data?
- What are some common challenges in selecting a suitable domain adaptation approach for a given LLM and new domain?
- How can we evaluate the effectiveness of domain adaptation and few-shot learning in adapting LLMs to new domains?
- What are some strategies for mitigating the effects of domain drift and adaptation in LLMs, and how can we detect it?
- Can you discuss the trade-offs between fine-tuning, domain adaptation, and few-shot learning in adapting LLMs to new domains?
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