Model Releases
Public interpretability dataset and benchmark library for a novel transformer architecture [R]
This work presents an explainability library for transformer models that provides tools for understanding transformer behavior through attributions and concept-based explanations . The resource likely
This work presents an explainability library for transformer models that provides tools for understanding transformer behavior through attributions and concept-based explanations . The resource likely includes methods for splitting models, extracting activation datasets, learning interpretable concepts, and estimating their importance for predictions .
Source: r/MachineLearning | 2026-05-03