3 papers
stat.ML2026
Trustworthy Feature Importance Avoids Unrestricted Permutations
Emanuele Borgonovo, Francesco Cappelli, Xuefei Lu +2
Feature importance methods using unrestricted permutations are flawed due to extrapolation errors; such errors appear in all non-trivial variable importance approaches. We propose…
cs.CL2025
No for Some, Yes for Others: Persona Prompts and Other Sources of False Refusal in Language Models
Flor Miriam Plaza-del-Arco, Paul Röttger, Nino Scherrer +3
Large language models (LLMs) are increasingly integrated into our daily lives and personalized. However, LLM personalization might also increase unintended side effects. Recent wor…
stat.CO2025
gsaot: an R package for Optimal Transport-based sensitivity analysis
Leonardo Chiani, Emanuele Borgonovo, Elmar Plischke +1
gsaot is an R package for Optimal Transport-based global sensitivity analysis. It provides a simple interface for indices estimation using a variety of state-of-the-art Optimal Tra…