44 citations · 67 across the 9 of their papers we have counts for
9 papers
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…
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…
Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search
Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini
In this research work we present CLIP-GLaSS, a novel zero-shot framework to generate an image (or a caption) corresponding to a given caption (or image). CLIP-GLaSS is based on the…
Solving the scalarization issues of Advantage-based Reinforcement Learning Algorithms
Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini
In this research, some of the issues that arise from the scalarization of the multi-objective optimization problem in the Advantage Actor Critic (A2C) reinforcement learning algori…
Formal derivation of Mesh Neural Networks with their Forward-Only gradient Propagation
Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini
This paper proposes the Mesh Neural Network (MNN), a novel architecture which allows neurons to be connected in any topology, to efficiently route information. In MNNs, information…
Using stigmergy as a computational memory in the design of recurrent neural networks
Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini
In this paper, a novel architecture of Recurrent Neural Network (RNN) is designed and experimented. The proposed RNN adopts a computational memory based on the concept of stigmergy…
Using stigmergy to incorporate the time into artificial neural networks
Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini
A current research trend in neurocomputing involves the design of novel artificial neural networks incorporating the concept of time into their operating model. In this paper, a no…