3 papers
cs.LG2026
CEAR: Certified Ensemble Adversarial Robustness in DNNs
Daniel Sadig, Mohammadreza Maleki, Hamed Karimi +1
Deep Neural Networks (DNNs) are highly susceptible to adversarial perturbations, leading to extensive research on robustness for safety-critical applications. State-of-the-art empi…
cs.LG2026
LLMs Uncertainty Quantification via Adaptive Conformal Semantic Entropy
Hamed Karimi, Vaishali Meyappan, Reza Samavi
LLMs' overconfidence, particularly when hallucinating, poses a significant challenge for the deployment of the models in safety-critical settings and makes a reliable estimation of…
cs.LG2024
Evidential Uncertainty Sets in Deep Classifiers Using Conformal Prediction
Hamed Karimi, Reza Samavi
In this paper, we propose Evidential Conformal Prediction (ECP) method for image classifiers to generate the conformal prediction sets. Our method is designed based on a non-confor…