2 papers
cs.LG2025
Iterative In-Context Learning to Enhance LLMs Abstract Reasoning: The Case-Study of Algebraic Tasks
Stefano Fioravanti, Matteo Zavatteri, Roberto Confalonieri +4
LLMs face significant challenges in systematic generalization, particularly when dealing with reasoning tasks requiring compositional rules and handling out-of-distribution example…
cs.AI2025
Logic Explanation of AI Classifiers by Categorical Explaining Functors
Stefano Fioravanti, Francesco Giannini, Paolo Frazzetto +2
The most common methods in explainable artificial intelligence are post-hoc techniques which identify the most relevant features used by pretrained opaque models. Some of the most…