316 citations · 609 across the 44 of their papers we have counts for
51 papers
Least-time Gradient Flow
Alessandro Betti, Marco Gori, Stefano Melacci +1
Prescribing the speed of gradient flow on the risk itself, by the dynamics $\dot w=-u(E(w))\nabla E(w)/\abs{\nabla E(w)}^{2}$, makes the risk obey exa…
LTLZinc: a Benchmarking Framework for Continual Learning and Neuro-Symbolic Temporal Reasoning
Luca Salvatore Lorello, Nikolaos Manginas, Marco Lippi +1
Neuro-symbolic artificial intelligence aims to combine neural architectures with symbolic approaches that can represent knowledge in a human-interpretable formalism. Continual lear…
A Neuro-Symbolic Framework for Sequence Classification with Relational and Temporal Knowledge
Luca Salvatore Lorello, Marco Lippi, Stefano Melacci
One of the goals of neuro-symbolic artificial intelligence is to exploit background knowledge to improve the performance of learning tasks. However, most of the existing frameworks…
Generative System Dynamics in Recurrent Neural Networks
Michele Casoni, Tommaso Guidi, Alessandro Betti +2
In this study, we investigate the continuous time dynamics of Recurrent Neural Networks (RNNs), focusing on systems with nonlinear activation functions. The objective of this work…
Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases
Christian Di Maio, Cristian Cosci, Marco Maggini +2
The growing ubiquity of Retrieval-Augmented Generation (RAG) systems in several real-world services triggers severe concerns about their security. A RAG system improves the generat…
A Unified Framework for Neural Computation and Learning Over Time
Stefano Melacci, Alessandro Betti, Michele Casoni +3
This paper proposes Hamiltonian Learning, a novel unified framework for learning with neural networks "over time", i.e., from a possibly infinite stream of data, in an online manne…