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Related Questions
- What are the key differences between multi-task learning and transfer learning in LLMs?
- How do LLMs adapt to new tasks during fine-tuning, and what role does domain adaptation play in this process?
- Can you explain the concept of task-specific and task-agnostic knowledge in LLMs, and how they relate to multi-task learning?
- What are some common techniques used to adapt LLMs to new domains, and how do they impact the model's performance?
- How do LLMs handle task conflicts during fine-tuning, such as when the tasks have different objectives or require different representations?
- What is the role of meta-learning in LLMs, and how does it facilitate transfer learning and domain adaptation?
- Can you provide an example of a scenario where multi-task learning and transfer learning are used together in a real-world application?
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