From the 1 of 5 linked papers with an AI index.
5 papers
HyperNet-Adaptation for Diffusion-Based Test Case Generation
Oliver WeiÃl, Vincenzo Riccio, Severin Kacianka +1
HyNeA introduces hypernetwork-based control of diffusion models to efficiently generate realistic, failure-inducing test cases without needing labeled datasets, reducing computatio…
Generative Testing of Automated Speech Recognition Systems
Yanis Xabier Wilbrand Peña, Oliver WeiÃl, Andrea Stocco
Automatic speech recognition (ASR) systems have achieved high accuracy with transformer-based models, enabling deployment in critical applications. However, they remain vulnerable…
Latent Regularization in Generative Test Input Generation
Giorgi Merabishvili, Oliver WeiÃl, Andrea Stocco
This study investigates the impact of regularization of latent spaces through truncation on the quality of generated test inputs for deep learning classifiers. We evaluate this eff…
Feature-Aware Test Generation for Deep Learning Models
Xingcheng Chen, Oliver Weissl, Andrea Stocco
As deep learning models are widely used in software systems, test generation plays a crucial role in assessing the quality of such models before deployment. To date, the most advan…
Targeted Deep Learning System Boundary Testing
Oliver WeiÃl, Amr Abdellatif, Xingcheng Chen +4
Evaluating the behavioral boundaries of deep learning (DL) systems is crucial for understanding their reliability across diverse, unseen inputs. Existing solutions fall short as th…