34 citations · 113 across the 36 of their papers we have counts for
5 papers · 1 filter
Unraveling the Key Components of OOD Generalization via Diversification
Harold Benoit, Liangze Jiang, Andrei Atanov +3
Supervised learning datasets may contain multiple cues that explain the training set equally well, i.e., learning any of them would lead to the correct predictions on the training…
Risk Aware Benchmarking of Large Language Models
Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti +6
We propose a distributional framework for benchmarking socio-technical risks of foundation models with quantified statistical significance. Our approach hinges on a new statistical…
DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications
Adam Ivankay, Mattia Rigotti, Pascal Frossard
Along with the successful deployment of deep neural networks in several application domains, the need to unravel the black-box nature of these networks has seen a significant incre…
Adaptive Conformal Regression with Jackknife+ Rescaled Scores
Nicolas Deutschmann, Mattia Rigotti, Maria Rodriguez Martinez
Conformal regression provides prediction intervals with global coverage guarantees, but often fails to capture local error distributions, leading to non-homogeneous coverage. We ad…
Auditing and Generating Synthetic Data with Controllable Trust Trade-offs
Brian Belgodere, Pierre Dognin, Adam Ivankay +11
Real-world data often exhibits bias, imbalance, and privacy risks. Synthetic datasets have emerged to address these issues. This paradigm relies on generative AI models to generate…