12 citations · 42 across the 10 of their papers we have counts for
4 papers · 1 filter
Mechanistic understanding and validation of large AI models with SemanticLens
Maximilian Dreyer, Jim Berend, Tobias Labarta +4
Unlike human-engineered systems such as aeroplanes, where each component's role and dependencies are well understood, the inner workings of AI models remain largely opaque, hinderi…
Explainable AI for Time Series via Virtual Inspection Layers
Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon +1
The field of eXplainable Artificial Intelligence (XAI) has greatly advanced in recent years, but progress has mainly been made in computer vision and natural language processing. F…
Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees
Johanna Vielhaben, Stefan Blücher, Nils Strodthoff
The completeness axiom renders the explanation of a post-hoc XAI method only locally faithful to the model, i.e. for a single decision. For the trustworthy application of XAI, in p…
Sparse Subspace Clustering for Concept Discovery (SSCCD)
Johanna Vielhaben, Stefan Blücher, Nils Strodthoff
Concepts are key building blocks of higher level human understanding. Explainable AI (XAI) methods have shown tremendous progress in recent years, however, local attribution method…