3 papers
cs.CL2026
Eliciting Intrinsic Hallucinations in LLMs via Semantically Equivalent Adversarial Attacks
Atri Vivek Sharma, Brian Formento, Alessio Lomuscio
Large language models (LLMs) are often used in conjunction with external knowledge sources to improve their factual accuracy and decrease hallucinations, through methods such as Re…
cs.AI2026
Formal Verification of Agentic Systems over Operational Data
Alejandro J. Mercado, Alessio Lomuscio
Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world workflows where they act on persistent operational data. Before deployment, these sys…
cs.LG2025
Verification of Neural Networks against Convolutional Perturbations via Parameterised Kernels
Benedikt Brückner, Alessio Lomuscio
We develop a method for the efficient verification of neural networks against convolutional perturbations such as blurring or sharpening. To define input perturbations we use well-…