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Related Questions
- What are the key challenges in adapting NLP models to specific domains?
- How do domain adaptation techniques address the problem of out-of-domain data in NLP?
- Can you explain the concept of domain-invariant features and its role in domain adaptation?
- What are some common techniques used for domain adaptation in NLP, such as multi-task learning and adversarial training?
- How do domain adaptation techniques help to reduce the domain gap between training and testing data?
- What are some real-world applications of domain adaptation in NLP, such as sentiment analysis and named entity recognition?
- How can domain adaptation techniques be used to improve the performance of NLP models in low-resource languages?
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