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Related Questions
- Can feature importance measures help identify biased factors that contribute to unfair treatment in text summarization models?
- How can the feature importance scores of individual words or phrases reveal information about the model's decision-making process?
- In what ways can analyzing feature importance scores of certain words or topics improve the transparency of text summarization models?
- Are there any limitations to relying solely on feature importance to evaluate the fairness of text summarization models?
- Can feature importance scores be used to pinpoint potential biases in the model's representation of different populations or groups?
- How can feature importance inform the development of more balanced and representative training datasets for text summarization models?
- Can feature importance scores be used to create explanations for the summarization outputs, enhancing model transparency and trustworthiness?
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