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Related Questions
- How does multi-task learning improve the transferability of learned features across tasks?
- Can you elaborate on the benefits of pre-training LLMs on a diverse set of tasks versus fine-tuning on a single task?
- How does joint training on multiple tasks using shared or distinct models compare to training separate models on individual tasks?
- What are the trade-offs between model capacity and task complexity in multi-task learning for LLMs?
- Can you discuss the importance of task selection and prioritization in multi-task learning for complex tasks?
- How can meta-learning be integrated with multi-task learning to further enhance the generalizability of LLMs?
- What are the implications of multi-task learning for LLM interpretability, and how can methods such as feature importance attribution help with this challenge?
- How do ensemble methods, such as stacked or hierarchical models, enhance the robustness of multi-task LLMs in complex scenarios?
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