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Related Questions
- What are the primary factors that contribute to the trade-off between model performance and robustness in adversarial training for LLMs?
- How do different adversarial training methods, such as PGD and FGSM, impact the trade-off between model performance and robustness in LLMs?
- What are the implications of overfitting on the trade-off between model performance and robustness in adversarial training for LLMs?
- Can you discuss the role of regularization techniques, such as dropout and weight decay, in mitigating the trade-off between model performance and robustness in LLMs?
- How does the choice of optimizer and learning rate affect the trade-off between model performance and robustness in adversarial training for LLMs?
- What are the benefits and limitations of using transfer learning and fine-tuning in the context of adversarial training for LLMs, and how do they impact the trade-off between model performance and robustness?
- Can you explain the concept of robustness metrics, such as robust accuracy and robustness metrics, and how they can be used to evaluate the trade-off between model performance and robustness in LLMs?
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