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Related Questions
- How can permutation importance be used to identify biases in text summarization models that favor certain topics or entities over others?
- Can permutation importance help detect biases in text summarization models that result in unequal representation of different groups or demographics?
- In what ways can permutation importance be applied to identify biases in text summarization models that produce summaries with different tone or sentiment?
- How can permutation importance be used to evaluate the fairness of text summarization models in real-world scenarios, such as news articles or social media posts?
- What are some potential challenges or limitations of using permutation importance to detect biases in text summarization models?
- Can permutation importance be used to identify biases in text summarization models that result in unequal representation of different languages or dialects?
- How can permutation importance be used to evaluate the robustness of text summarization models to biases in the training data?
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