168 citations · 288 across the 9 of their papers we have counts for
10 papers
Neural Bayesian Networks for Modular and Scalable Decision-Making Under Uncertainty
Giovanni Briglia, Marco Lippi, Stefano Mariani +1
Bayesian Networks (BNs) are established tools for letting agents reason under uncertainty in sequential decision-making. They split a joint distribution into local conditional mech…
Individual and Collective Autonomous Development
Marco Lippi, Stefano Mariani, Matteo Martinelli +1
The increasing complexity and unpredictability of many ICT scenarios let us envision that future systems will have to dynamically learn how to act and adapt to face evolving situat…
Combining Transformers with Natural Language Explanations
Federico Ruggeri, Marco Lippi, Paolo Torroni
Many NLP applications require models to be interpretable. However, many successful neural architectures, including transformers, still lack effective interpretation methods. A poss…
Tree-Constrained Graph Neural Networks For Argument Mining
Federico Ruggeri, Marco Lippi, Paolo Torroni
We propose a novel architecture for Graph Neural Networks that is inspired by the idea behind Tree Kernels of measuring similarity between trees by taking into account their common…
Parallelizing Machine Learning as a Service for the End-User
Daniela Loreti, Marco Lippi, Paolo Torroni
As ML applications are becoming ever more pervasive, fully-trained systems are made increasingly available to a wide public, allowing end-users to submit queries with their own dat…
Neural-Symbolic Argumentation Mining: an Argument in Favor of Deep Learning and Reasoning
Andrea Galassi, Kristian Kersting, Marco Lippi +2
Deep learning is bringing remarkable contributions to the field of argumentation mining, but the existing approaches still need to fill the gap toward performing advanced reasoning…
Predicting the Usefulness of Amazon Reviews Using Off-The-Shelf Argumentation Mining
Marco Passon, Marco Lippi, Giuseppe Serra +1
Internet users generate content at unprecedented rates. Building intelligent systems capable of discriminating useful content within this ocean of information is thus becoming a ur…
CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service
Marco Lippi, Przemyslaw Palka, Giuseppe Contissa +4
Terms of service of on-line platforms too often contain clauses that are potentially unfair to the consumer. We present an experimental study where machine learning is employed to…
Natural Language Statistical Features of LSTM-generated Texts
Marco Lippi, Marcelo A Montemurro, Mirko Degli Esposti +1
Long Short-Term Memory (LSTM) networks have recently shown remarkable performance in several tasks dealing with natural language generation, such as image captioning or poetry comp…
Learning to see like children: proof of concept
Marco Gori, Marco Lippi, Marco Maggini +1
In the last few years we have seen a growing interest in machine learning approaches to computer vision and, especially, to semantic labeling. Nowadays state of the art systems use…