15 papers
Reusing Operational Evidence After Context Changes: A Conservative Bayesian Framework for Autonomous Vehicle Safety
Robab Aghazadeh Chakherlou, Siddartha Khastgir, Xingyu Zhao
Operational evidence, i.e., evidence of operation without failure is an important component of confidence in the safety or reliability of a system in service, but it is costly to c…
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…
Probabilistic Robustness in Medical Image Classification
Yi Zhang, Siddartha Khastgir, Xingyu Zhao
Deep learning (DL) has shown strong performance in medical image classification, but its trustworthy deployment remains challenging in safety-critical clinical settings, where pred…
Non-Parametric Probabilistic Robustness: A Conservative Risk Estimator under Unknown Perturbation Distributions
Zheng Wang, Yi Zhang, Siddartha Khastgir +2
Deep learning (DL) models, despite their remarkable success, remain vulnerable to small input perturbations that can cause erroneous outputs, motivating the recent proposal of prob…
PRBench: A Standardized Probabilistic Robustness Benchmark
Yi Zhang, Zheng Wang, Zhen Chen +5
Deep learning models are notoriously vulnerable to imperceptible perturbations. Most existing research centers on adversarial robustness (AR), which evaluates models under worst-ca…
Toward Safe and Energy-Efficient 5G NR V2X Communications in Rural Environments
Zhanle Zhao, Son Dinh-Van, Yuen Kwan Mo +2
Connected braking can reduce fatal collisions in connected and autonomous vehicles (CAVs) by using reliable, low-latency 5G New Radio (NR) links, especially NR Sidelink Vehicle-to-…