From the 1 of 9 linked papers with an AI index.
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Smaller Models, Unexpected Costs: Trade-offs in LLM Quantization for Automated Program Repair
Fernando Vallecillos-Ruiz, Giordano d'Aloisio, Max Hort +3
Large Language Models (LLMs) are powerful tools and have been increasingly adopted for complex software engineering tasks. As the number of parameters increases, results can often…
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…
How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias
Tosin Fadahunsi, Giordano d'Aloisio, Antinisca Di Marco +1
Generative models are nowadays widely used to generate graphical content used for multiple purposes, e.g. web, art, advertisement. However, it has been shown that the images genera…
Investigating the Role of LLMs Hyperparameter Tuning and Prompt Engineering to Support Domain Modeling
Vladyslav Bulhakov, Giordano d'Aloisio, Claudio Di Sipio +2
The introduction of large language models (LLMs) has enhanced automation in software engineering tasks, including in Model Driven Engineering (MDE). However, using general-purpose…
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…
On the Compression of Language Models for Code: An Empirical Study on CodeBERT
Giordano d'Aloisio, Luca Traini, Federica Sarro +1
Language models have proven successful across a wide range of software engineering tasks, but their significant computational costs often hinder their practical adoption. To addres…