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Related Questions
- What are the primary factors that contribute to the success of transfer learning in enhancing the generalizability of large language models (LLMs)?
- Which pre-training tasks are most effective in promoting the transferability of LLMs across different domains and tasks?
- How do the choice of pre-training data and the size of the pre-training corpus impact the generalizability of LLMs in transfer learning settings?
- What role do domain adaptation techniques play in improving the transferability of LLMs to new, unseen tasks and domains?
- Can you explain the concept of 'domain knowledge' and its importance in the context of transfer learning for LLMs?
- How do the differences in task-specific objectives and evaluation metrics affect the transferability of LLMs across various tasks and domains?
- What are some common pitfalls or challenges that practitioners may encounter when applying transfer learning to LLMs, and how can they be addressed?
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