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Related Questions
- What are the potential biases in pre-trained models that can affect their performance?
- How can data quality issues in pre-trained models impact their accuracy and reliability?
- What are the risks of overfitting in pre-trained models, and how can they be addressed?
- Can pre-trained models be vulnerable to adversarial attacks, and if so, how can they be protected?
- How can the lack of diversity in pre-trained models' training data affect their performance on diverse datasets?
- What are the potential risks of using pre-trained models in high-stakes applications, such as healthcare or finance?
- How can the interpretability of pre-trained models be improved to understand their decision-making processes?
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