204 citations · 207 across the 7 of their papers we have counts for
7 papers
Statistical Foundations of DIME: Risk Estimation for Practical Index Selection
Giulio D'Erasmo, Cesare Campagnano, Antonio Mallia +3
High-dimensional dense embeddings have become central to modern Information Retrieval, but many dimensions are noisy or redundant. Recently proposed DIME (Dimension IMportance Esti…
Enhancing XAI Narratives through Multi-Narrative Refinement and Knowledge Distillation
Flavio Giorgi, Matteo Silvestri, Cesare Campagnano +2
Explainable Artificial Intelligence has become a crucial area of research, aiming to demystify the decision-making processes of deep learning models. Among various explainability t…
Natural Language Counterfactual Explanations for Graphs Using Large Language Models
Flavio Giorgi, Cesare Campagnano, Fabrizio Silvestri +1
Explainable Artificial Intelligence (XAI) has emerged as a critical area of research to unravel the opaque inner logic of (deep) machine learning models. Among the various XAI tech…
: Gradient-based and Task-Agnostic machine Unlearning
Daniel Trippa, Cesare Campagnano, Maria Sofia Bucarelli +2
Machine Unlearning, the process of selectively eliminating the influence of certain data examples used during a model's training, has gained significant attention as a means for pr…
The Power of Noise: Redefining Retrieval for RAG Systems
Florin Cuconasu, Giovanni Trappolini, Federico Siciliano +5
Retrieval-Augmented Generation (RAG) has recently emerged as a method to extend beyond the pre-trained knowledge of Large Language Models by augmenting the original prompt with rel…
Prompt-to-OS (P2OS): Revolutionizing Operating Systems and Human-Computer Interaction with Integrated AI Generative Models
Gabriele Tolomei, Cesare Campagnano, Fabrizio Silvestri +1
In this paper, we present a groundbreaking paradigm for human-computer interaction that revolutionizes the traditional notion of an operating system. Within this innovative framewo…
CycleDRUMS: Automatic Drum Arrangement For Bass Lines Using CycleGAN
Giorgio Barnabò, Giovanni Trappolini, Lorenzo Lastilla +4
The two main research threads in computer-based music generation are: the construction of autonomous music-making systems, and the design of computer-based environments to assist m…