Papers by Aki-Juhani Kyröläinen

1 papers
Explaining Classes through Stable Word Attributions (2022.findings-acl)

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Challenge: Input saliency methods have become popular for explaining predictions of deep learning models, but there has been little work investigating methods for aggregating prediction-level explanations to the class level.
Approach: They propose a method to aggregate prediction-level explanations to the class level using XLM-R and Integrated Gradients input attribution methods.
Outcome: The proposed method extracts keyword lists of classes from text classification tasks and evaluates them on web register data.

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