262 citations · 358 across the 27 of their papers we have counts for
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cs.AI2023
GInX-Eval: Towards In-Distribution Evaluation of Graph Neural Network Explanations
Kenza Amara, Mennatallah El-Assady, Rex Ying
Diverse explainability methods of graph neural networks (GNN) have recently been developed to highlight the edges and nodes in the graph that contribute the most to the model predi…
cs.AI2022★ 2 cited
Visual Comparison of Language Model Adaptation
Rita Sevastjanova, Eren Cakmak, Shauli Ravfogel +2
Neural language models are widely used; however, their model parameters often need to be adapted to the specific domains and tasks of an application, which is time- and resource-co…