3 citations · 9 across the 19 of their papers we have counts for
8 papers · 1 filter
Predicting human cooperation: sensitizing drift-diffusion model to interaction and external stimuli
Lucila G. Alvarez-Zuzek, Laura Ferrarotti, Bruno Lepri +1
As humans perceive and actively engage with the world, we adjust our decisions in response to shifting group dynamics and are influenced by social interactions. This study aims to…
SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
Mátyás Vincze, Laura Ferrarotti, Leonardo Lucio Custode +2
Continuous control tasks often involve high-dimensional, dynamic, and non-linear environments. State-of-the-art performance in these tasks is achieved through complex closed-box po…
Towards Civic Digital Twins: Co-Design the Citizen-Centric Future of Bologna
Massimiliano Luca, Bruno Lepri, Riccardo Gallotti +3
We introduce Civic Digital Twin (CDT), an evolution of Urban Digital Twins designed to support a citizen-centric transformative approach to urban planning and governance. CDT is be…
Do LLMs suffer from Multi-Party Hangover? A Diagnostic Approach to Addressee Recognition and Response Selection in Conversations
Nicolò Penzo, Maryam Sajedinia, Bruno Lepri +2
Assessing the performance of systems to classify Multi-Party Conversations (MPC) is challenging due to the interconnection between linguistic and structural characteristics of conv…
Separation Power of Equivariant Neural Networks
Marco Pacini, Xiaowen Dong, Bruno Lepri +1
The separation power of a machine learning model refers to its ability to distinguish between different inputs and is often used as a proxy for its expressivity. Indeed, knowing th…
Large Language Models are Zero-Shot Next Location Predictors
Ciro Beneduce, Bruno Lepri, Massimiliano Luca
Predicting the locations an individual will visit in the future is crucial for solving many societal issues like disease diffusion and reduction of pollution. However, next-locatio…
Putting Context in Context: the Impact of Discussion Structure on Text Classification
Nicolò Penzo, Antonio Longa, Bruno Lepri +2
Current text classification approaches usually focus on the content to be classified. Contextual aspects (both linguistic and extra-linguistic) are usually neglected, even in tasks…
A Characterization Theorem for Equivariant Networks with Point-wise Activations
Marco Pacini, Xiaowen Dong, Bruno Lepri +1
Equivariant neural networks have shown improved performance, expressiveness and sample complexity on symmetrical domains. But for some specific symmetries, representations, and cho…