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Related Questions
- What are the key challenges in fine-tuning dialogue models using traditional supervised learning?
- How does few-shot learning address the issue of limited labeled data in dialogue model fine-tuning?
- What are the main differences in the training objectives between traditional supervised learning and few-shot learning in dialogue model fine-tuning?
- Can you explain the role of meta-learning in few-shot learning for dialogue model fine-tuning?
- How does few-shot learning enable dialogue models to adapt to new domains or tasks with minimal data?
- What are the potential applications of few-shot learning in dialogue model fine-tuning, such as in customer service or voice assistants?
- How does few-shot learning compare to other transfer learning techniques, such as domain adaptation or multi-task learning, in the context of dialogue model fine-tuning?
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