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Related Questions
- What are some strategies for fine-tuning large language models on domain-specific datasets while minimizing overfitting and maintaining generalizability?
- How can we balance the trade-off between adapting large language models to specific domains and ensuring they remain effective in unseen data?
- What are some techniques for avoiding domain-specific adaptation from negatively impacting a model's ability to generalize to other domains?
- Can you discuss the importance of regularizing large language models to prevent over-specialization in domain adaptation?
- What are some methods for evaluating the generalizability of large language models after domain-specific adaptation?
- How can we use transfer learning to adapt large language models to new domains while preserving their general knowledge?
- What are some techniques for using multi-task learning to improve the generalizability of large language models in domain adaptation?
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