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Related Questions
- What are the primary challenges associated with using transfer learning for domain adaptation in text generation models?
- How does the concept of 'domain shift' impact the performance of transfer learning-based text generation models?
- What are some common limitations of using pre-trained language models for domain adaptation, and how can they be mitigated?
- What is the role of data augmentation in addressing domain adaptation challenges in text generation models?
- Can you discuss the trade-off between fine-tuning and retraining from scratch in the context of domain adaptation for text generation models?
- How can transfer learning-based text generation models be adapted to handle out-of-domain data and maintain their performance?
- What are some strategies for selecting the most suitable pre-trained model for a specific domain adaptation task in text generation?
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