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Related Questions
- What are the common techniques used to calculate feature importance in text summarization models?
- How do different feature importance methods (e.g. permutation importance, SHAP, LIME) compare in terms of interpretability and accuracy?
- Can you explain the concept of feature interaction in text summarization models and how it relates to feature importance?
- How do feature importance methods handle out-of-vocabulary words or rare words in text summarization models?
- Can you discuss the relationship between feature importance and model interpretability in text summarization?
- What are some common challenges in evaluating feature importance in text summarization models, and how can they be addressed?
- How can feature importance methods be used to improve the explainability of text summarization models in real-world applications?
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