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Related Questions
- What is the primary concept behind knowledge distillation and how does it relate to LLMs?
- Can you elaborate on the mechanisms by which knowledge distillation helps to prevent forgetting in large language models?
- How does the training process for knowledge distillation differ from traditional fine-tuning, and what implications does this have for mitigating forgetting?
- In what ways do knowledge distillation and transfer learning intersect, and how might they be combined to leverage existing knowledge in LLMs?
- Are there any challenges associated with implementing knowledge distillation in real-world scenarios, and if so, what strategies might be employed to address these?
- To what extent do the gains in preventing forgetting via knowledge distillation rely on the quality of the knowledge used for distillation, and how might high-quality knowledge be acquired for this purpose?
- What are some experimental designs for evaluating the impact of knowledge distillation on LLMs' forgetfulness, and what quantitative metrics could be used to assess the effectiveness of knowledge distillation in this regard?
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