3 citations · 9 across the 19 of their papers we have counts for
22 papers
Observe, Share, or Predict? Disentangling Partner Information in Embodied Multi-Agent Collaboration
Adrián Szlatincsán, Filippo Ziliotto, Bruno Lepri +3
LLMs are used as high-level controllers for embodied agents, but it remains unclear whether they support collaborative reasoning, such as anticipating a collaborator's actions in r…
Deal Me Maybe: The Role of Emotions in Multi-Agent Negotiation
Massimiliano Luca, Apoorva Singh, Bruno Lepri
Negotiation is a demanding social task for LLM agents, requiring strategic reasoning, persuasion, and interpersonal adaptation. Yet existing benchmarks often treat agents as emotio…
Ant swarm functional control via stigmergic Reinforcement Learning agents
Alessio Pitteri, Andrea Guizzo, Laura Ferrarotti +2
In this work, we propose a novel framework for the functional controllability of the ant swarm model, a well-known and relevant model of collective behaviour. Our approach introduc…
Mirror, Mirror on the Wall: Can VLM Agents Tell Who They Are at All?
Filippo Ziliotto, Ciro Beneduce, Bruno Lepri +3
In the animal kingdom, mirror self-recognition is a canonical probe of higher-order cognition, emerging only in some species. We ask whether an analogous functional capability emer…
LLMberjack: Guided Trimming of Debate Trees for Multi-Party Conversation Creation
Leonardo Bottona, Nicolò Penzo, Bruno Lepri +2
We present LLMberjack, a platform for creating multi-party conversations starting from existing debates, originally structured as reply trees. The system offers an interactive inte…
On Universality of Deep Equivariant Networks
Marco Pacini, Mircea Petrache, Bruno Lepri +2
Universality results for equivariant neural networks remain rare. Those that do exist typically hold only in restrictive settings: either they rely on regular or higher-order tenso…
TS-Mob: Social and Geographical-Aware Time Series Foundation-Model Framework for Human Mobility Prediction
Massimiliano Luca, Ciro Beneduce, Bruno Lepri
Short-term forecasting of aggregated human mobility flows supports urban planning, intelligent transportation systems, and emergency response, yet existing models often require sub…
AI's Blind Spots: Geographic Knowledge and Diversity Deficit in Generated Urban Scenario
Ciro Beneduce, Massimiliano Luca, Bruno Lepri
Diffusion-based text-to-image models are increasingly used for urban analysis and scenario generation, but their geographic knowledge and representational biases remain poorly unde…
pySpainMobility: Unlocking Spanish Open Mobility Data for Spatial Inequality Research
Ciro Beneduce, Tania Gullón Muñoz-Repiso, Bruno Lepri +1
Human mobility shapes access to resources, opportunities, and services, making movement data a powerful lens for studying spatial and social inequality. Yet despite the growing ava…
On Universality Classes of Equivariant Networks
Marco Pacini, Gabriele Santin, Bruno Lepri +1
Equivariant neural networks provide a principled framework for incorporating symmetry into learning architectures and have been extensively analyzed through the lens of their separ…
The LLM Wears Prada: Analysing Gender Bias and Stereotypes through Online Shopping Data
Massimiliano Luca, Ciro Beneduce, Bruno Lepri +1
With the wide and cross-domain adoption of Large Language Models, it becomes crucial to assess to which extent the statistical correlations in training data, which underlie their i…
Multimodal Large Language Models Predict Urban Safety Perception but Encode Non-Neutral Demographic Priors
Ciro Beneduce, Bruno Lepri, Massimiliano Luca
Understanding how people perceive urban environments is essential for inclusive planning, yet conventional surveys are costly and difficult to scale. We investigate whether Multimo…
Don't Stop the Multi-Party! On Generating Synthetic Written Multi-Party Conversations with Constraints
Nicolò Penzo, Marco Guerini, Bruno Lepri +2
Written Multi-Party Conversations (WMPCs) are widely studied across disciplines, with social media as a primary data source due to their accessibility. However, these datasets rais…
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…
Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation
Laura Ferrarotti, Massimiliano Luca, Gabriele Santin +9
Optimizing traffic dynamics in an evolving transportation landscape is crucial, particularly in scenarios where autonomous vehicles (AVs) with varying levels of autonomy coexist wi…