14 citations · 15 across the 8 of their papers we have counts for
8 papers
When Text and Numbers Disagree: Evidence Arbitration in Large Language Models
Mattia Carletti, Edward Phillips, Fredrik K. Gustafsson +5
Large language models (LLMs) are increasingly used in settings where textual summaries, numerical observations, and external tool outputs may provide conflicting evidence. We study…
Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons
Wei Tang, Jinpei Han, Kangning Cui +10
Electrocardiogram (ECG) foundation models pretrained on typical diagnostic 10-second ECG segments, have demonstrated strong transferability across a range of clinical applications.…
SignalMC-MED: A Multimodal Benchmark for Evaluating Biosignal Foundation Models on Single-Lead ECG and PPG
Fredrik K. Gustafsson, Xiao Gu, Mattia Carletti +3
Recent biosignal foundation models (FMs) have demonstrated promising performance across diverse clinical prediction tasks, yet systematic evaluation on long-duration multimodal dat…
On the Properties of Adversarially-Trained CNNs
Mattia Carletti, Matteo Terzi, Gian Antonio Susto
Adversarial Training has proved to be an effective training paradigm to enforce robustness against adversarial examples in modern neural network architectures. Despite many efforts…
AcME -- Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box
David Dandolo, Chiara Masiero, Mattia Carletti +2
In the context of human-in-the-loop Machine Learning applications, like Decision Support Systems, interpretability approaches should provide actionable insights without making the…
Improving Robustness with Image Filtering
Matteo Terzi, Mattia Carletti, Gian Antonio Susto
Adversarial robustness is one of the most challenging problems in Deep Learning and Computer Vision research. All the state-of-the-art techniques require a time-consuming procedure…
Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing
Alessandro Fabris, Alan Mishler, Stefano Gottardi +4
We conduct an audit of pricing algorithms employed by companies in the Italian car insurance industry, primarily by gathering quotes through a popular comparison website. While ack…
Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance
Mattia Carletti, Matteo Terzi, Gian Antonio Susto
Anomaly Detection is an unsupervised learning task aimed at detecting anomalous behaviours with respect to historical data. In particular, multivariate Anomaly Detection has an imp…