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Related Questions
- What is the purpose of saliency maps in transformer-based models, and how do they help improve interpretability?
- Can you explain the different types of saliency maps and their applications in transformer-based models?
- How do saliency maps help in identifying the most important features or tokens that contribute to the model's predictions?
- What are the challenges and limitations of using saliency maps in transformer-based models, and how can they be addressed?
- Can you provide examples of real-world applications where saliency maps have improved the interpretability of transformer-based models?
- How do saliency maps compare to other interpretability methods, such as feature importance or partial dependence plots, in transformer-based models?
- What are some potential future directions for improving the interpretability of transformer-based models using saliency maps?
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