Efficient Statistical Assessment of Neural Network Corruption Robustness. - Karim Tit; Teddy Furon; Mathias Rousset (NeurIPS, 2021)

Gradient-Informed Neural Network Statistical Robustness Estimation. - Karim Tit; Teddy Furon; Mathias Rousset (AISTATS, 2023)

Three Bricks to Consolidate Watermarks for Large Language Models. - Pierre Fernandez; Antoine Chaffin; Karim Tit; Vivien Chappelier; Teddy Furon (WIFS, 2023)

Fast Reliability Estimation for Neural Networks with Adversarial Attack-Driven Importance Sampling. - Karim Tit; Teddy Furon (UAI, 2024)

Reliability of Deep Learning with Rare Event Simulation :Theory and Practice. (Fiabilité du Deep Learning avec simulation d'événements rares :théorie et pratique). - Karim Tit (2024)

On the Robustness of Tabular Foundation Models: Test-Time Attacks and In-Context Defenses. - Mohamed Djilani; Thibault Simonetto; Karim Tit; Florian Tambon; Paul Récamier; Salah Ghamizi; Maxime Cordy; Mike Papadakis (CoRR, 2025)

TRIDENT: Temporally Restricted Inference via DFA-Enhanced Neural Traversal. - Vincenzo Collura; Karim Tit; Laura Bussi; Eleonora Giunchiglia; Maxime Cordy (CoRR, 2025)

KCLNet: Physics-Informed Power Flow Prediction via Constraints Projections. - Pantelis Dogoulis; Karim Tit; Maxime Cordy (CoRR, 2025)

Constraint-Guided Prediction Refinement via Deterministic Diffusion Trajectories. - Pantelis Dogoulis; Fabien Bernier; Félix Fourreau; Karim Tit; Maxime Cordy (CoRR, 2025)