180 citations · 368 across the 30 of their papers we have counts for
32 papers
Learning neuro-symbolic convergent term rewriting systems
Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti
Building neural systems that can learn to execute symbolic algorithms is a challenging open problem in artificial intelligence, especially when aiming for strong generalization and…
A Spectral Interpretation of Redundancy in a Graph Reservoir
Anna Bison, Alessandro Sperduti
Reservoir computing has been successfully applied to graphs as a preprocessing method to improve the training efficiency of Graph Neural Networks (GNNs). However, a common issue th…
From Text to Talent: A Pipeline for Extracting Insights from Candidate Profiles
Paolo Frazzetto, Muhammad Uzair Ul Haq, Flavia Fabris +1
The recruitment process is undergoing a significant transformation with the increasing use of machine learning and natural language processing techniques. While previous studies ha…
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto +5
Albeit the ubiquitous use of Graph Neural Networks (GNNs) in machine learning (ML) prediction tasks involving graph-structured data, their interpretability remains challenging. In…
IFH: a Diffusion Framework for Flexible Design of Graph Generative Models
Samuel Cognolato, Alessandro Sperduti, Luciano Serafini
Graph generative models can be classified into two prominent families: one-shot models, which generate a graph in one go, and sequential models, which generate a graph by successiv…
Assessing the Emergent Symbolic Reasoning Abilities of Llama Large Language Models
Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti
Large Language Models (LLMs) achieve impressive performance in a wide range of tasks, even if they are often trained with the only objective of chatting fluently with users. Among…