3 papers
cs.SE2026
The CAISAR Platform: Extending the Reach of Machine Learning Specification and Verification
Michele Alberti, François Bobot, Julien Girard-Satabin +3
The formal specification and verification of machine learning programs saw remarkable progress in less than a decade, leading to a profusion of tools. However, diversity may lead t…
cs.AI2025
Formal Abductive Latent Explanations for Prototype-Based Networks
Jules Soria, Zakaria Chihani, Julien Girard-Satabin +3
Case-based reasoning networks are machine-learning models that make predictions based on similarity between the input and prototypical parts of training samples, called prototypes.…
cs.AI2024
CaBRNet, an open-source library for developing and evaluating Case-Based Reasoning Models
Romain Xu-Darme, Aymeric Varasse, Alban Grastien +2
In the field of explainable AI, a vibrant effort is dedicated to the design of self-explainable models, as a more principled alternative to post-hoc methods that attempt to explain…