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Related Questions
- What are the key differences between pre-training and fine-tuning in large-scale language models?
- How does the size of the pre-training dataset affect a language model's ability to capture domain-specific knowledge?
- Can you explain the concept of 'domain adaptation' in the context of large-scale language models?
- What are some common techniques used to inject domain-specific knowledge into a pre-trained language model?
- How does the choice of pre-training task (e.g. masked language modeling, next sentence prediction) impact a language model's ability to capture domain-specific knowledge?
- Can you discuss the trade-offs between pre-training a language model on a large general-domain dataset versus a smaller domain-specific dataset?
- What are some potential challenges and limitations of using large-scale pre-training to capture domain-specific knowledge?
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