activity
20242026
most citedArtificial Intelligence in Everyday Life 2.0: Educating University Students from Different Majors

13 citations · 33 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval

Hao Xu, Rite Bo, Fausto Giunchiglia +2

Although studies have demonstrated that Large Language Models (LLMs) can perform well on Out-of-Distribution (OOD) tasks, their advantage tends to diminish as the distribution shif…

cs.LG2025

Help the machine to help you: an evaluation in the wild of egocentric data cleaning via skeptical learning

Andrea Bontempelli, Matteo Busso, Leonardo Javier Malcotti +1

Any digital personal assistant, whether used to support task performance, answer questions, or manage work and daily life, including fitness schedules, requires high-quality annota…

cs.CY2025★ 6 cited

Understanding Gen Alpha Digital Language: Evaluation of LLM Safety Systems for Content Moderation

Manisha Mehta, Fausto Giunchiglia

This research offers a unique evaluation of how AI systems interpret the digital language of Generation Alpha (Gen Alpha, born 2010-2024). As the first cohort raised alongside AI,…

cs.HC2025

Towards Open Diversity-Aware Social Interactions

Loizos Michael, Ivano Bison, Matteo Busso +15

Social Media and the Internet have catalyzed an unprecedented potential for exposure to human diversity in terms of demographics, talents, opinions, knowledge, and the like. Howeve…

cs.CY2025★ 12 cited

DiversityOne: A Multi-Country Smartphone Sensor Dataset for Everyday Life Behavior Modeling

Matteo Busso, Andrea Bontempelli, Leonardo Javier Malcotti +23

Understanding everyday life behavior of young adults through personal devices, e.g., smartphones and smartwatches, is key for various applications, from enhancing the user experien…

cs.CL2024★ 2 cited

Shortcut Learning in In-Context Learning: A Survey

Rui Song, Yingji Li, Lida Shi +2

Shortcut learning refers to the phenomenon where models employ simple, non-robust decision rules in practical tasks, which hinders their generalization and robustness. With the rap…

cs.CY2024★ 13 cited

Artificial Intelligence in Everyday Life 2.0: Educating University Students from Different Majors

Maria Kasinidou, Styliani Kleanthous, Matteo Busso +3

With the surge in data-centric AI and its increasing capabilities, AI applications have become a part of our everyday lives. However, misunderstandings regarding their capabilities…