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Revealing Unfair Models by Mining Interpretable Evidence
The key idea is to find solid evidence in the form of a group of data instances discriminated most by the model.
Robust Counterfactual Explanations on Graph Neural Networks
Massive deployment of Graph Neural Networks (GNNs) in high-stake applications generates a strong demand for explanations that are robust to noise and align well with human intuition.
G3raphGround: Graph-Based Language Grounding
In this paper we present an end-to-end framework for grounding of phrases in images.
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