49 citations · 189 across the 32 of their papers we have counts for
12 papers · 1 filter
Learning to Guide Human Experts via Personalized Large Language Models
Debodeep Banerjee, Stefano Teso, Andrea Passerini
In learning to defer, a predictor identifies risky decisions and defers them to a human expert. One key issue with this setup is that the expert may end up over-relying on the mach…
Egocentric Hierarchical Visual Semantics
Luca Erculiani, Andrea Bontempelli, Andrea Passerini +1
We are interested in aligning how people think about objects and what machines perceive, meaning by this the fact that object recognition, as performed by a machine, should follow…
Interval Logic Tensor Networks
Samy Badreddine, Gianluca Apriceno, Andrea Passerini +1
In this paper, we introduce Interval Real Logic (IRL), a two-sorted logic that interprets knowledge such as sequential properties (traces) and event properties using sequences of r…
Neuro-Symbolic Reasoning Shortcuts: Mitigation Strategies and their Limitations
Emanuele Marconato, Stefano Teso, Andrea Passerini
Neuro-symbolic predictors learn a mapping from sub-symbolic inputs to higher-level concepts and then carry out (probabilistic) logical inference on this intermediate representation…
Enhancing SMT-based Weighted Model Integration by Structure Awareness
Giuseppe Spallitta, Gabriele Masina, Paolo Morettin +2
The development of efficient exact and approximate algorithms for probabilistic inference is a long-standing goal of artificial intelligence research. Whereas substantial progress…
SMT-based Weighted Model Integration with Structure Awareness
Giuseppe Spallitta, Gabriele Masina, Paolo Morettin +2
Weighted Model Integration (WMI) is a popular formalism aimed at unifying approaches for probabilistic inference in hybrid domains, involving logical and algebraic constraints. Des…
Lifelong Personal Context Recognition
Andrea Bontempelli, Marcelo Rodas Britez, Xiaoyue Li +5
We focus on the development of AIs which live in lifelong symbiosis with a human. The key prerequisite for this task is that the AI understands - at any moment in time - the person…
Towards Visual Semantics
Fausto Giunchiglia, Luca Erculiani, Andrea Passerini
Lexical Semantics is concerned with how words encode mental representations of the world, i.e., concepts . We call this type of concepts, classification concepts . In this paper, w…
Constructive Preference Elicitation over Hybrid Combinatorial Spaces
Paolo Dragone, Stefano Teso, Andrea Passerini
Preference elicitation is the task of suggesting a highly preferred configuration to a decision maker. The preferences are typically learned by querying the user for choice feedbac…
Coactive Critiquing: Elicitation of Preferences and Features
Stefano Teso, Paolo Dragone, Andrea Passerini
When faced with complex choices, users refine their own preference criteria as they explore the catalogue of options. In this paper we propose an approach to preference elicitation…
Learning Modulo Theories for preference elicitation in hybrid domains
Paolo Campigotto, Roberto Battiti, Andrea Passerini
This paper introduces CLEO, a novel preference elicitation algorithm capable of recommending complex objects in hybrid domains, characterized by both discrete and continuous attrib…
Structured Learning Modulo Theories
Stefano Teso, Roberto Sebastiani, Andrea Passerini
Modelling problems containing a mixture of Boolean and numerical variables is a long-standing interest of Artificial Intelligence. However, performing inference and learning in hyb…