3 accepted papers
Checking the reliability of machine-learning models is a crucial, but challenging task. Nomos is an existing, automated framework for testing general, user-provided functional properties of models, including so-called hyperproperties expressed over more than one model execution. Nomos aims to find m
Large language models are becoming increasingly practical for translating code across programming languages, a process known as transpiling. Even though automated transpilation significantly boosts developer productivity, a key concern is whether the generated code is correct. Existing work initiall…
Machine-learning models are becoming increasingly prevalent in our lives, for instance assisting in image-classification or decision-making tasks. Consequently, the reliability of these models is of critical importance and has resulted in the development of numerous approaches for validating and ver…