39 citations · 45 across the 11 of their papers we have counts for
4 papers · 1 filter
Underrepresentation, Label Bias, and Proxies: Towards Data Bias Profiles for the EU AI Act and Beyond
Marina Ceccon, Giandomenico Cornacchia, Davide Dalle Pezze +2
Undesirable biases encoded in the data are key drivers of algorithmic discrimination. Their importance is widely recognized in the algorithmic fairness literature, as well as legis…
MAD-MAX: Modular And Diverse Malicious Attack MiXtures for Automated LLM Red Teaming
Stefan Schoepf, Muhammad Zaid Hameed, Ambrish Rawat +4
With LLM usage rapidly increasing, their vulnerability to jailbreaks that create harmful outputs are a major security risk. As new jailbreaking strategies emerge and models are cha…
Counterfactual Fair Opportunity: Measuring Decision Model Fairness with Counterfactual Reasoning
Giandomenico Cornacchia, Vito Walter Anelli, Fedelucio Narducci +2
The increasing application of Artificial Intelligence and Machine Learning models poses potential risks of unfair behavior and, in light of recent regulations, has attracted the at…
Counterfactual Reasoning for Bias Evaluation and Detection in a Fairness under Unawareness setting
Giandomenico Cornacchia, Vito Walter Anelli, Fedelucio Narducci +2
Current AI regulations require discarding sensitive features (e.g., gender, race, religion) in the algorithm's decision-making process to prevent unfair outcomes. However, even wit…