1 citations · 3 across the 6 of their papers we have counts for
8 papers
Generative AI-Based Data Augmentation for Oral Lesion Classification: The PhotoMOCI Dataset and Benchmark
Marco Parola, Mario G. C. A. Cimino, Sabrina Senatore
Early detection of oral cancer via photographic imaging presents a promising avenue for large-scale oral cavity screening. However, the development of robust deep learning models i…
Assessing Alignment and Stability of Feature Importance Explanations via Weight of Evidence
Eddie Conti, Claudio Daka, Álvaro Parafita +3
Feature importance Methods (FIMs) are widely used in Explainable AI to interpret model predictions, yet attribution scores alone often provide limited insight into the underlying r…
A Mentalistic Interface for Probing Folk-Psychological Attribution to Non-Humanoid Robots
Giulio Pisaneschi, Pierpaolo Serio, Estelle Gerbier +3
This paper presents an experimental platform for studying intentional-state attribution toward a non-humanoid robot. The system combines a simulated robot, realistic task environme…
Interpretable Machine Learning for Oral Lesion Diagnosis through Prototypical Instances Identification
Alessio Cascione, Mattia Setzu, Federico A. Galatolo +2
Decision-making processes in healthcare can be highly complex and challenging. Machine Learning tools offer significant potential to assist in these processes. However, many curren…
Improving Small-Scale Large Language Models Function Calling for Reasoning Tasks
Graziano A. Manduzio, Federico A. Galatolo, Mario G. C. A. Cimino +2
Recent advancements in Large Language Models (LLMs) have demonstrated exceptional capabilities in natural language understanding and generation. While these models excel in general…
A machine learning workflow to address credit default prediction
Rambod Rahmani, Marco Parola, Mario G. C. A. Cimino
Due to the recent increase in interest in Financial Technology (FinTech), applications like credit default prediction (CDP) are gaining significant industrial and academic attentio…
Cerbero-7B: A Leap Forward in Language-Specific LLMs Through Enhanced Chat Corpus Generation and Evaluation
Federico A. Galatolo, Mario G. C. A. Cimino
This study introduces a novel approach for generating high-quality, language-specific chat corpora using a self-chat mechanism. We combine a generator LLM for creating new samples…
TeTIm-Eval: a novel curated evaluation data set for comparing text-to-image models
Federico A. Galatolo, Mario G. C. A. Cimino, Edoardo Cogotti
Evaluating and comparing text-to-image models is a challenging problem. Significant advances in the field have recently been made, piquing interest of various industrial sectors. A…