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Related Questions
- How does regularization help prevent catastrophic forgetting in language models, and what are the key mechanisms involved?
- Can you explain the concept of regularization in the context of language models, and how it relates to the problem of catastrophic forgetting?
- What types of regularization techniques are commonly used to mitigate catastrophic forgetting in language models, and what are their strengths and weaknesses?
- How does regularization affect the trade-off between model capacity and overfitting in language models, and what implications does this have for mitigating catastrophic forgetting?
- Can you discuss the role of regularization in preventing the forgetting of previously learned tasks in language models, and how it compares to other approaches such as transfer learning?
- What are some best practices for implementing regularization techniques to mitigate catastrophic forgetting in language models, and what are some common pitfalls to avoid?
- How does the choice of regularization technique impact the performance of language models on downstream tasks, and what are some strategies for selecting the most effective regularization approach?
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