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Related Questions
- What are the key factors that contribute to the exploration-exploitation trade-off in active learning for NLP and how do they impact the performance of the model?
- How can we quantify the trade-off between exploration and exploitation in active learning for NLP and what are the implications for query selection?
- What are some common methods for balancing the exploration-exploitation trade-off in active learning for NLP and how do they affect the diversity of query selection?
- Can you explain the concept of uncertainty sampling and its relationship to the exploration-exploitation trade-off in active learning for NLP?
- How can we use techniques such as Thompson sampling and upper confidence bound applied to bounds (UCB) to balance exploration and exploitation in active learning for NLP?
- What are some challenges in balancing the exploration-exploitation trade-off in active learning for NLP and how can we address them to improve diversity in query selection?
- Can you discuss the role of human-in-the-loop in balancing the exploration-exploitation trade-off in active learning for NLP and how it can improve the diversity of query selection?
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