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Related Questions
- What are the key differences between supervised and unsupervised domain adaptation in transfer learning?
- How does domain adaptation help bridge the performance gap between high-resource and low-resource languages in machine translation tasks?
- What are some common techniques used for domain adaptation in low-resource languages, such as language model fine-tuning and adversarial training?
- Can you provide examples of successful domain adaptation applications in low-resource languages, such as language translation and sentiment analysis?
- How does domain adaptation relate to multilingual learning, and what are its benefits for low-resource languages?
- What are the challenges and limitations of domain adaptation in low-resource languages, and how can they be addressed?
- How does domain adaptation compare to other transfer learning techniques, such as few-shot learning and meta-learning, in the context of low-resource languages?
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