3 papers
cs.LG2025
Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation
Boqi Chen, Kristóf Marussy, Oszkár Semeráth +2
Graph convolutional neural networks (GCNs) are powerful tools for learning graph-based knowledge representations from training data. However, they are vulnerable to small perturbat…
cs.SE2025
ALPINE: An adaptive language-agnostic pruning method for language models for code
Mootez Saad, José Antonio Hernández López, Boqi Chen +2
Language models of code have demonstrated state-of-the-art performance across various software engineering and source code analysis tasks. However, their demanding computational re…
cs.SE2024
Automated and Complete Generation of Traffic Scenarios at Road Junctions Using a Multi-level Danger Definition
Aren A. Babikian, Attila Ficsor, Oszkár Semeráth +2
To ensure their safe use, autonomous vehicles (AVs) must meet rigorous certification criteria that involve executing maneuvers safely within (arbitrary) scenarios where other actor…