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Related Questions
- What are the key differences between supervised and unsupervised learning in the context of pre-training?
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- What role do contextual representations play in enabling the transfer of knowledge across different domains?
- Can you explain the concept of 'zero-shot' learning and how pre-training enables it?
- In what ways do pre-trained models learn to generalize across different tasks and domains?
- How does the choice of pre-training objective affect the transferability of knowledge across different domains?
- What are some common challenges that arise when fine-tuning pre-trained models on new domains, and how can they be addressed?
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