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Related Questions
- How does transfer learning help large language models adapt to new tasks with minimal training data?
- Can you explain the concept of pre-training and fine-tuning in the context of transfer learning for large language models?
- What are some common techniques used to adapt pre-trained language models to new tasks, and how do they impact generalization?
- How does the choice of pre-training objective and architecture affect the ability of large language models to generalize to new tasks?
- What role does domain adaptation play in enabling large language models to generalize to new tasks, and how is it related to transfer learning?
- Can you discuss the trade-offs between task-specific training and transfer learning for large language models, and when each approach is most effective?
- How do large language models leverage prior knowledge and experience to generalize to new tasks, and what are some challenges associated with this process?
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