activity
20232026
most citedUnsupervised Concept Drift Detection from Deep Learning Representations in Real-time

34 citations · 39 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2026

When AI Enters the Workplace, Who Faces Greater Risks? A Gendered Analysis

Miriam Fernandez, Ángel Pavón Pérez, Damiano Giallongo +4

Gender inequality remains a persistent structural feature of the labour market, shaping women's lifetime earnings and economic security. As artificial intelligence (AI) transforms…

cs.CY2026

Will AI Agents Free Us From Meaningless Work? A Human-Centered Analysis

Davide Ghia, Jaspreet Ranjit, Tania Cerquitelli +1

Some claim that AI agents will free workers from the boring parts of their jobs, yet little is known about how workers themselves identify which tasks should be automated. Prior re…

cs.CL2024★ 5 cited

NLPGuard: A Framework for Mitigating the Use of Protected Attributes by NLP Classifiers

Salvatore Greco, Ke Zhou, Licia Capra +2

AI regulations are expected to prohibit machine learning models from using sensitive attributes during training. However, the latest Natural Language Processing (NLP) classifiers,…

cs.LG2024★ 34 cited

Unsupervised Concept Drift Detection from Deep Learning Representations in Real-time

Salvatore Greco, Bartolomeo Vacchetti, Daniele Apiletti +1

Concept drift is the phenomenon in which the underlying data distributions and statistical properties of a target domain change over time, leading to a degradation in model perform…

cs.HC2023

Conversational Data Exploration: A Game-Changer for Designing Data Science Pipelines

Genoveva Vargas-Solar, Tania Cerquitelli, Javier A. Espinosa-Oviedo +3

This paper proposes a conversational approach implemented by the system Chatin for driving an intuitive data exploration experience. Our work aims to unlock the full potential of d…