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Related Questions
- What are the key strategies for selecting representative data in active learning for adapting language models to regional dialects?
- How does uncertainty sampling and core set selection work in active learning for regional dialect adaptation, and what are their pros and cons?
- What are the advantages of using transfer learning and meta-learning in active learning for regional dialect adaptation with limited training data?
- Can you provide examples of successful applications of active learning in adapting language models to regional dialects in languages like Spanish, Mandarin, or Arabic?
- How can you incorporate real-time feedback from human annotators or end-users in the active learning process for regional dialect adaptation?
- What are the trade-offs between using synthetic data augmentation and real data collection for regional dialect adaptation with active learning?
- What are the most important performance metrics to evaluate the success of active learning for regional dialect adaptation in a given domain?
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