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Related Questions
- What are the key differences between in-domain and out-of-domain text generation, and how does domain adaptation address these differences?
- Can you explain the concept of domain shift and how it affects the performance of text generation models?
- How does the size of the training dataset impact the ability of a text generation model to generalize to new, unseen domains?
- What are some common techniques used to adapt text generation models to new domains, and how do they relate to the size of the training dataset?
- In what ways can a large training dataset help to reduce the domain adaptation gap in text generation?
- Can you discuss the trade-offs between increasing the size of the training dataset and improving the performance of a text generation model in a new domain?
- How does the concept of 'domain knowledge' relate to the effectiveness of domain adaptation in text generation, and how can a larger training dataset help to capture this knowledge?
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