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Concept-based vision models represent images through an intermediate layer of human-inspectable concepts, so what a model relies on can be traced to those concepts. However, those models are often limited to fixed categories or depend on language to define their concepts. We introduce DisParQ (Discrete Parts with Quant...
When a graph neural network (GNN) explainer produces an unexpected attribution on a molecule, the attribution alone cannot reveal whether the explainer has failed or the model has learned a shortcut. We introduce WOMBAT, a benchmark of 14 whitebox GNNs, each with message-passing weights set by hand to detect a specific...
The Spatial Relation Recognition Task (SpaRRTa) benchmark is introduced, which evaluates the ability of VFMs to identify relative positions of objects in the image and provides insights into the mechanisms that support or hinder spatial awareness in modern VFMs.
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