Sentence-Based Model Agnostic NLP Interpretability. - Yves Rychener; Xavier Renard; Djamé Seddah; Pascal Frossard; Marcin Detyniecki (CoRR, 2020)

QUACKIE: A NLP Classification Task With Ground Truth Explanations. - Yves Rychener; Xavier Renard; Djamé Seddah; Pascal Frossard; Marcin Detyniecki (CoRR, 2020)

On the Granularity of Explanations in Model Agnostic NLP Interpretability. - Yves Rychener; Xavier Renard; Djamé Seddah; Pascal Frossard; Marcin Detyniecki (PKDD/ECML Workshops (1), 2022)

Metrizing Fairness. - Yves Rychener; Bahar Taskesen; Daniel Kuhn 001 (CoRR, 2022)

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective. - Yves Rychener; Daniel Kuhn 001; Tobias Sutter (ICML, 2023)

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set. - Man-Chung Yue; Yves Rychener; Daniel Kuhn 001; Viet Anh Nguyen (CoRR, 2024)

Global Group Fairness in Federated Learning via Function Tracking. - Yves Rychener; Daniel Kuhn 001; Yifan Hu (AISTATS, 2025)