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Related Questions
- How do diversity and representativeness affect the performance of active learning in NLP?
- What are the benefits and drawbacks of prioritizing diversity over representativeness, or vice versa, in query selection?
- Can you provide examples of scenarios where diversity is more important than representativeness, and vice versa?
- How do different metrics, such as entropy and uncertainty, impact the trade-off between diversity and representativeness?
- What role does the size of the labeled dataset play in the trade-off between diversity and representativeness?
- Are there any techniques or algorithms that can automatically balance the trade-off between diversity and representativeness?
- How does the trade-off between diversity and representativeness impact the overall performance and generalizability of the NLP model?
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