Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Ragone, Azzurra"'
Autor:
Lops, Andrea, Narducci, Fedelucio, Ragone, Azzurra, Trizio, Michelantonio, Bartolini, Claudio
Unit tests represent the most basic level of testing within the software testing lifecycle and are crucial to ensuring software correctness. Designing and creating unit tests is a costly and labor-intensive process that is ripe for automation. Recent
Externí odkaz:
http://arxiv.org/abs/2408.07846
Autor:
Baldassarre, Maria Teresa, Gigante, Domenico, Kalinowski, Marcos, Ragone, Azzurra, Tibidò, Sara
Publikováno v:
28th International Conference on Evaluation and Assessment in Software Engineering (EASE 2024), June 18-21, 2024, Salerno, Italy
Recently, there has been growing attention on behalf of both academic and practice communities towards the ability of Artificial Intelligence (AI) systems to operate responsibly and ethically. As a result, a plethora of frameworks and guidelines have
Externí odkaz:
http://arxiv.org/abs/2407.12135
Autor:
Baldassarre, Maria T., Caivano, Danilo, Nieto, Berenice Fernandez, Gigante, Domenico, Ragone, Azzurra
Publikováno v:
Proceedings of the 2023 ACM Conference on Information Technology for Social Good (GoodIT '23)
In recent months, the social impact of Artificial Intelligence (AI) has gained considerable public interest, driven by the emergence of Generative AI models, ChatGPT in particular. The rapid development of these models has sparked heated discussions
Externí odkaz:
http://arxiv.org/abs/2403.04667
Publikováno v:
Conference on AI Engineering Software Engineering for AI (CAIN 2024), April 14--15, 2024, Lisbon, Portugal
In the ever-expanding landscape of Artificial Intelligence (AI), where innovation thrives and new products and services are continuously being delivered, ensuring that AI systems are designed and developed responsibly throughout their entire lifecycl
Externí odkaz:
http://arxiv.org/abs/2402.05340
Publikováno v:
Proceedings of the International Conference on Evaluation and Assessment in Software Engineering (EASE '23), June 14--16, 2023, Oulu, Finland
In the last years, the raise of Artificial Intelligence (AI), and its pervasiveness in our lives, has sparked a flourishing debate about the ethical principles that should lead its implementation and use in society. Driven by these concerns, we condu
Externí odkaz:
http://arxiv.org/abs/2306.05003
Autor:
Cornacchia, Giandomenico, Anelli, Vito Walter, Narducci, Fedelucio, Ragone, Azzurra, Di Sciascio, Eugenio
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 without sensitive features in the training set, algorithms can persist in
Externí odkaz:
http://arxiv.org/abs/2302.08204
Autor:
Cornacchia, Giandomenico, Anelli, Vito Walter, Narducci, Fedelucio, Ragone, Azzurra, Di Sciascio, Eugenio
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 attention of the research community. Several researchers focused on seek
Externí odkaz:
http://arxiv.org/abs/2302.08158
Model-based approaches to recommendation can recommend items with a very high level of accuracy. Unfortunately, even when the model embeds content-based information, if we move to a latent space we miss references to the actual semantics of recommend
Externí odkaz:
http://arxiv.org/abs/1909.05038
Hyper-parameters tuning is a crucial task to make a model perform at its best. However, despite the well-established methodologies, some aspects of the tuning remain unexplored. As an example, it may affect not just accuracy but also novelty as well
Externí odkaz:
http://arxiv.org/abs/1909.02523
Autor:
Cornacchia, Giandomenico, Anelli, Vito Walter, Biancofiore, Giovanni Maria, Narducci, Fedelucio, Pomo, Claudio, Ragone, Azzurra, Di Sciascio, Eugenio
Publikováno v:
In Information Processing and Management March 2023 60(2)
