6 papers
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…
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…
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…
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,…
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…
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…