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Related Questions
- What are feature importance scores and how are they calculated in the context of summarization models?
- How can feature importance scores be used to identify the most influential input features for a summarization model?
- Can feature importance scores be used to compare the performance of different summarization models on the same dataset?
- How can feature importance scores help identify areas for improvement in a summarization model, such as underperforming input features or biased outputs?
- What are some common challenges or limitations when using feature importance scores to compare summarization models and improve their performance?
- Can feature importance scores be used to evaluate the robustness of a summarization model to different input data distributions or noise levels?
- How can feature importance scores be used to identify opportunities for model interpretability and explainability in summarization models?
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