4 papers
SCOPE: A Dataset of Stereotyped Prompts for Counterfactual Fairness Assessment of LLMs
Alessandra Parziale, Gianmario Voria, Valeria Pontillo +3
Large Language Models (LLMs) now serve as the foundation for a wide range of applications, from conversational assistants to decision support tools, making the issue of fairness in…
Once Upon a Team: Investigating Bias in LLM-Driven Software Team Composition and Task Allocation
Alessandra Parziale, Gianmario Voria, Valeria Pontillo +4
LLMs are increasingly used to boost productivity and support software engineering tasks. However, when applied to socially sensitive decisions such as team composition and task all…
Toward Systematic Counterfactual Fairness Evaluation of Large Language Models: The CAFFE Framework
Alessandra Parziale, Gianmario Voria, Valeria Pontillo +3
Nowadays, Large Language Models (LLMs) are foundational components of modern software systems. As their influence grows, concerns about fairness have become increasingly pressing.…
Contextual Fairness-Aware Practices in ML: A Cost-Effective Empirical Evaluation
Alessandra Parziale, Gianmario Voria, Giammaria Giordano +3
As machine learning (ML) systems become central to critical decision-making, concerns over fairness and potential biases have increased. To address this, the software engineering (…