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Related Questions
- Can data augmentation improve the interpretability of large language models by enhancing feature importance and saliency maps?
- How does data augmentation affect the feature importance scores of large language models in terms of magnitude and ranking?
- Does data augmentation influence the activation patterns of neurons in large language models, and if so, how?
- Can data augmentation lead to more robust feature importance and saliency maps in large language models?
- How does the type of data augmentation (e.g., word dropout, paraphrasing, etc.) impact the feature importance and saliency maps of large language models?
- Can data augmentation be used to identify and reduce feature importance and saliency map artifacts in large language models?
- How does the amount of data augmentation (e.g., number of augmented samples) affect the feature importance and saliency maps of large language models?
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