3 citations · 3 across the 5 of their papers we have counts for
6 papers
Causal Routing for Unlearning
Bardh Prenkaj, Andrea D'Angelo, Davide Mottin +4
LLMs cannot forget the way we delete a file. Strangely, we are asked to remove something that was never put anywhere in particular. What the model took from a piece of text is now…
Beyond Binary Rewards: A Comparative Study of Reward Design for Reinforcement Unlearning
Efstratios Zaradoukas, Davide Gabrielli, Bardh Prenkaj +1
Machine unlearning seeks to selectively remove specific knowledge from trained language models without full retraining, a growing necessity under privacy regulations such as GDPR a…
A Multi-Agent Framework for Interpreting Multivariate Physiological Time Series
Davide Gabrielli, Paola Velardi, Stefano Faralli +1
Continuous physiological monitoring is central to emergency care, yet deploying trustworthy AI is challenging. While LLMs can translate complex physiological signals into clinical…
Inverse Language Modeling towards Robust and Grounded LLMs
Davide Gabrielli, Simone Sestito, Iacopo Masi
The current landscape of defensive mechanisms for LLMs is fragmented and underdeveloped, unlike prior work on classifiers. To further promote adversarial robustness in LLMs, we pro…
AI on the Pulse: Real-Time Health Anomaly Detection with Wearable and Ambient Intelligence
Davide Gabrielli, Bardh Prenkaj, Paola Velardi +1
We introduce AI on the Pulse, a real-world-ready anomaly detection system that continuously monitors patients using a fusion of wearable sensors, ambient intelligence, and advanced…
Seamless Monitoring of Stress Levels Leveraging a Universal Model for Time Sequences
Davide Gabrielli, Bardh Prenkaj, Paola Velardi
Monitoring the stress level in patients with neurodegenerative diseases can help manage symptoms, improve patient's quality of life, and provide insight into disease progression. I…