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Related Questions
- Can active learning be used to identify ambiguous or uncertain inputs in conversational AI, and how?
- How do sampling strategies and query strategies contribute to the effectiveness of active learning in noisy dialogue data?
- What is the role of human evaluators in active learning, and how can their judgment be incorporated into the selection process?
- What techniques can be used to evaluate the effectiveness of active learning in noisy dialogue systems, such as metrics and evaluation frameworks?
- How can active learning strategies be adapted for real-world applications, considering factors such as data sparsity, distribution shift, and multi-task learning?
- What are some common limitations and challenges associated with implementing active learning in dialogue systems, and how can they be addressed?
- Can active learning be integrated with other approaches, like reinforcement learning, to address the noisy data problem in dialogue systems?
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