3 papers
stat.ML2024
Attention Meets Post-hoc Interpretability: A Mathematical Perspective
Gianluigi Lopardo, Frederic Precioso, Damien Garreau
Attention-based architectures, in particular transformers, are at the heart of a technological revolution. Interestingly, in addition to helping obtain state-of-the-art results on…
cs.CL2023
Faithful and Robust Local Interpretability for Textual Predictions
Gianluigi Lopardo, Frederic Precioso, Damien Garreau
Interpretability is essential for machine learning models to be trusted and deployed in critical domains. However, existing methods for interpreting text models are often complex,…
stat.ML2023
Understanding Post-hoc Explainers: The Case of Anchors
Gianluigi Lopardo, Frederic Precioso, Damien Garreau
In many scenarios, the interpretability of machine learning models is a highly required but difficult task. To explain the individual predictions of such models, local model-agnost…