|  | Vol-3839 urn:nbn:de:0074-3839-8 Copyright © 2024 for the individual papers by the papers' authors. Copyright © 2024 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# XAI.it 2024
Italian Workshop on Explainable Artificial Intelligence 2024

### Proceedings of the 5th Italian Workshop on Explainable Artificial Intelligence,
co-located with the 23rd International Conference of the Italian Association for Artificial Intelligence

### Bolzano, Italy,November 26-27, 2024.

Edited by

### Marco Polignano *
Cataldo Musto *
Roberto Pellungrini **
Erasmo Purificato *** ‡
Giovanni Semeraro *
Mattia Setzu **

* University of Bari Aldo Moro, Italy
** Scuola Normale Superiore, Italy
*** Joint Research Centre, European Commission, Ispra, Italy
‡ The author contributed to this work while affiliated with Otto von Guericke University Magdeburg, Germany. The view expressed in this paper is purely that of the author and may not, under any circumstances, be regarded as an official position of the European Commission.

## Table of Contents

- Preface
  Summary: There were 8 papers submitted for peer-review to this workshop. Out of these, 6 papers were accepted for this volume, 5 as regular papers and 1 as short papers.

### Organizers Overview

- XAI.it 2024: An Overview on the Future of AI in the Era of Large Language Models 1-10
  Marco Polignano, Cataldo Musto, Roberto Pellungrini, Erasmo Purificato, Giovanni Semeraro, Mattia Setzu

### Oral Presentations

- A Comprehensive Strategy to Bias and Mitigation in Human Resource Decision Systems 11-27
  Silvia D’Amicantonio, Mishal Kizhakkam Kulangara, Het Darshan Mehta, Shalini Pal, Marco Levantesi, Marco Polignano, Erasmo Purificato, Ernesto William De Luca
- An Analysis on How Pre-Trained Language Models Learn Different Aspects 28-41
  Ejdis Gjinika, Nicola Arici, Luca Putelli, Alfonso E. Gerevini, Ivan Serina
- Ethical AI Systems and Shared Accountability: The Role of Economic Incentives in Fairness and Explainability (Short paper) 42-49
  Dae-Hyun Yoo, Caterina Giannetti
- ExplainBattery: Enhancing Battery Capacity Estimation with an Efficient LSTM Model and Explainability Features 50-64
  Leonardo Dal Ronco, Erasmo Purificato
- Using LLMs to explain AI-generated art classification via Grad-CAM heatmaps 65-74
  Giovanna Castellano, Maria Grazia Miccoli, Raffaele Scaringi, Gennaro Vessio, Gianluca Zaza
- Probabilistic Abstract Interpretation on Neural Networks via Grids Approximation 75-89
  Zhuofan Zhang, Herbert Wiklicky

2024-11-13: submitted by Marco Polignano, metadata incl. bibliographic data published under Creative Commons CC0
2024-11-22: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|