25 citations · 47 across the 10 of their papers we have counts for
10 papers
Legal Summarisation through LLMs: The PRODIGIT Project
Thiago Dal Pont, Federico Galli, Andrea Loreggia +3
We present some initial results of a large-scale Italian project called PRODIGIT which aims to support tax judges and lawyers through digital technology, focusing on AI. We have fo…
Learning Behavioral Soft Constraints from Demonstrations
Arie Glazier, Andrea Loreggia, Nicholas Mattei +3
Many real-life scenarios require humans to make difficult trade-offs: do we always follow all the traffic rules or do we violate the speed limit in an emergency? These scenarios fo…
When Is It Acceptable to Break the Rules? Knowledge Representation of Moral Judgement Based on Empirical Data
Edmond Awad, Sydney Levine, Andrea Loreggia +6
One of the most remarkable things about the human moral mind is its flexibility. We can make moral judgments about cases we have never seen before. We can decide that pre-establish…
Deep ensembles in bioimage segmentation
Loris Nanni, Daniela Cuza, Alessandra Lumini +2
Semantic segmentation consists in classifying each pixel of an image by assigning it to a specific label chosen from a set of all the available ones. During the last few years, a l…
Thinking Fast and Slow in AI
Grady Booch, Francesco Fabiano, Lior Horesh +8
This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making. The premise is that if we gain insights about the c…
Modeling Contrary-to-Duty with CP-nets
Roberta Calegari, Andrea Loreggia, Emiliano Lorini +2
In a ceteris-paribus semantics for deontic logic, a state of affairs where a larger set of prescriptions is respected is preferable to a state of affairs where some of them are vio…
Voting with Random Classifiers (VORACE): Theoretical and Experimental Analysis
Cristina Cornelio, Michele Donini, Andrea Loreggia +2
In many machine learning scenarios, looking for the best classifier that fits a particular dataset can be very costly in terms of time and resources. Moreover, it can require deep…
CPMetric: Deep Siamese Networks for Learning Distances Between Structured Preferences
Andrea Loreggia, Nicholas Mattei, Francesca Rossi +1
Preference are central to decision making by both machines and humans. Representing, learning, and reasoning with preferences is an important area of study both within computer sci…
Logical Conditional Preference Theories
Cristina Cornelio, Andrea Loreggia, Vijay Saraswat
CP-nets represent the dominant existing framework for expressing qualitative conditional preferences between alternatives, and are used in a variety of areas including constraint s…
Restricted Manipulation in Iterative Voting: Convergence and Condorcet Efficiency
Umberto Grandi, Andrea Loreggia, Francesca Rossi +2
In collective decision making, where a voting rule is used to take a collective decision among a group of agents, manipulation by one or more agents is usually considered negative…