3 papers
cs.LG2025
A General Framework for Property-Driven Machine Learning
Thomas Flinkow, Marco Casadio, Colin Kessler +2
Neural networks have been shown to frequently fail to learn critical safety and correctness properties purely from data, highlighting the need for training methods that directly in…
cs.RO2025
Neural Network Verification for Gliding Drone Control: A Case Study
Colin Kessler, Ekaterina Komendantskaya, Marco Casadio +5
As machine learning is increasingly deployed in autonomous systems, verification of neural network controllers is becoming an active research domain. Existing tools and annual veri…
cs.CL2025
NLP Verification: Towards a General Methodology for Certifying Robustness
Marco Casadio, Tanvi Dinkar, Ekaterina Komendantskaya +6
Machine Learning (ML) has exhibited substantial success in the field of Natural Language Processing (NLP). For example large language models have empirically proven to be capable o…