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Related Questions
- What are the key factors that influence data quality in active learning for NLP, and how does it impact model performance?
- How does data diversity impact the effectiveness of active learning in NLP, and what are the potential consequences of insufficient diversity?
- Can you explain the concept of 'out-of-distribution' data in NLP and how data quality and diversity relate to its impact on model performance?
- What are some strategies for ensuring data quality and diversity in active learning for NLP, and how can they be implemented in practice?
- How does the relationship between data quality, diversity, and out-of-distribution data affect model performance in real-world NLP applications?
- Can you provide examples of how poor data quality and diversity can lead to poor model performance on out-of-distribution data in NLP?
- What are some best practices for collecting and annotating high-quality, diverse data for active learning in NLP, and how can they be used to improve model performance?
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