1 citations · 1 across the 4 of their papers we have counts for
4 papers
Modeling Memory-Dependent Reliability of LLMs: A Hidden Markov Model
Robab Aghazadeh Chakherlou, Siddartha Khastgir, Peter Popov +1
Reliability assessment of large language models (LLMs) seeks to estimate the probability that a model produces correct responses under a specified operational profile. Conventional…
A Hierarchical Imprecise Probability Approach to Reliability Assessment of Large Language Models
Robab Aghazadeh-Chakherlou, Qing Guo, Siddartha Khastgir +3
Large Language Models (LLMs) are increasingly deployed across diverse domains, raising the need for rigorous reliability assessment methods. Existing benchmark-based evaluations pr…
Stochastic Modeling of Road Hazards on Intersections and their Effect on Safety of Autonomous Vehicles
Peter Popov, Lorenzo Strigini, Cornelius Buerkle +2
Autonomous vehicles (AV) look set to become common on our roads within the next few years. However, to achieve the final breakthrough, not only functional progress is required, but…
Evaluation of Confidence-based Ensembling in Deep Learning Image Classification
Rafael Rosales, Peter Popov, Michael Paulitsch
Ensembling is a successful technique to improve the performance of machine learning (ML) models. Conf-Ensemble is an adaptation to Boosting to create ensembles based on model confi…