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Found 4 papers, 3 papers with code
Learnings from Technological Interventions in a Low Resource Language: Enhancing Information Access in Gondi
The primary obstacle to developing technologies for low-resource languages is the lack of representative, usable data.
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
In addition, by restricting the features that can be modified for generating counterfactual examples, we find that the top-k features from LIME or SHAP are often neither necessary nor sufficient explanations of a model's prediction.
Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi
The primary obstacle to developing technologies for low-resource languages is the lack of usable data.
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations
Post-hoc explanations of machine learning models are crucial for people to understand and act on algorithmic predictions.
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