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Related Questions
- What are the common pitfalls when fine-tuning large language models on a new domain, and how can they be addressed?
- How do domain adaptation techniques, such as transfer learning and multi-task learning, impact the performance of large language models in unseen domains?
- What are the key factors that influence the effectiveness of domain adaptation, and how can they be optimized for better performance?
- Can you discuss the trade-offs between domain adaptation and model complexity, and how to balance them for optimal performance?
- What are some strategies for mitigating the impact of catastrophic forgetting when adapting large language models to new domains?
- How can knowledge distillation techniques be applied to adapt large language models to new domains while preserving their performance?
- What are some evaluation metrics and benchmarks for assessing the performance of large language models in unseen domains, and how can they be used to guide domain adaptation?
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