2 citations · 8 across the 9 of their papers we have counts for
9 papers
SafeTune: Search-based Harmfulness Minimisation for Large Language Models
Giordano d'Aloisio, David Williams, Giusy Annunziata +3
The widespread adoption of Large Language Models (LLMs) raises concerns about the potential harmfulness of their responses. In this paper, we first investigate the harmfulness of r…
A Generalised Exponentiated Gradient Approach to Enhance Fairness in Binary and Multi-class Classification Tasks
Maryam Boubekraoui, Giordano d'Aloisio, Antinisca Di Marco
The widespread use of AI and ML models in sensitive areas raises significant concerns about fairness. While the research community has introduced various methods for bias mitigatio…
VAMP: Visual Analytics for Microservices Performance
Luca Traini, Jessica Leone, Giovanni Stilo +1
Analysis of microservices' performance is a considerably challenging task due to the multifaceted nature of these systems. Each request to a microservices system might raise severa…
How fair are we? From conceptualization to automated assessment of fairness definitions
Giordano d'Aloisio, Claudio Di Sipio, Antinisca Di Marco +1
Fairness is a critical concept in ethics and social domains, but it is also a challenging property to engineer in software systems. With the increasing use of machine learning in s…
Data-Driven Analysis of Gender Fairness in the Software Engineering Academic Landscape
Giordano d'Aloisio, Andrea D'Angelo, Francesca Marzi +3
Gender bias in education gained considerable relevance in the literature over the years. However, while the problem of gender bias in education has been widely addressed from a stu…
Towards a Prediction of Machine Learning Training Time to Support Continuous Learning Systems Development
Francesca Marzi, Giordano d'Aloisio, Antinisca Di Marco +1
The problem of predicting the training time of machine learning (ML) models has become extremely relevant in the scientific community. Being able to predict a priori the training t…
A Decision Tree to Shepherd Scientists through Data Retrievability
Andrea Bianchi, Giordano d'Aloisio, Francesca Marzi +1
Reproducibility is a crucial aspect of scientific research that involves the ability to independently replicate experimental results by analysing the same data or repeating the sam…
Modeling Quality and Machine Learning Pipelines through Extended Feature Models
Giordano d'Aloisio, Antinisca Di Marco, Giovanni Stilo
The recently increased complexity of Machine Learning (ML) methods, led to the necessity to lighten both the research and industry development processes. ML pipelines have become a…
A model-driven approach to broaden the detection of software performance antipatterns at runtime
Antinisca Di Marco, Catia Trubiani
Performance antipatterns document bad design patterns that have negative influence on system performance. In our previous work we formalized such antipatterns as logical predicates…