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Found 6 papers, 5 papers with code
Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers
Our methodological contributions address two key prerequisites for concept-based alignment: 1) For a description of the representation in terms of concepts that faithfully capture the geometry of the feature space, we define concepts as the most general structure they can possibly form - arbitrary manifolds, allowing hidden features to be described by their proximity to these manifolds.
Quanda: An Interpretability Toolkit for Training Data Attribution Evaluation and Beyond
In recent years, training data attribution (TDA) methods have emerged as a promising direction for the interpretability of neural networks.
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression
Deep Neural Networks are prone to learning and relying on spurious correlations in the training data, which, for high-risk applications, can have fatal consequences.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Manipulating Feature Visualizations with Gradient Slingshots
Deep Neural Networks (DNNs) are capable of learning complex and versatile representations, however, the semantic nature of the learned concepts remains unknown.
Finding the right XAI method -- A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science
We find architecture-dependent performance differences regarding robustness, complexity and localization skills of different XAI methods, highlighting the necessity for research task-specific evaluation.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond
The evaluation of explanation methods is a research topic that has not yet been explored deeply, however, since explainability is supposed to strengthen trust in artificial intelligence, it is necessary to systematically review and compare explanation methods in order to confirm their correctness.
