250 citations · 335 across the 18 of their papers we have counts for
18 papers
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…
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…
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-…
Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation
Ben Batten, Yang Zheng, Alessandro De Palma +2
We address the problem of verifying neural networks against geometric transformations of the input image, including rotation, scaling, shearing, and translation. The proposed metho…
Tightening the Evaluation of PAC Bounds Using Formal Verification Results
Thomas Walker, Alessio Lomuscio
Probably Approximately Correct (PAC) bounds are widely used to derive probabilistic guarantees for the generalisation of machine learning models. They highlight the components of t…
Tight Verification of Probabilistic Robustness in Bayesian Neural Networks
Ben Batten, Mehran Hosseini, Alessio Lomuscio
We introduce two algorithms for computing tight guarantees on the probabilistic robustness of Bayesian Neural Networks (BNNs). Computing robustness guarantees for BNNs is a signifi…