Author

Natasha Sharygina

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Preprint Aug 2026

Termination analysis with interpolation-based transition invariant generation

Termination and nontermination of infinite-state systems are complementary problems that, despite their close connection, are typically addressed by separate techniques. The core idea of this paper is to connect termination and nontermination analysis, enabling the two to share intermediate results and guide one anothe...

Konstantin Britikov, Martin Blicha, Grigory Fedyukovich et al. · 0 citations

#machine learning Preprint Sep 2026

Neuron Activation-based Computation of Logical Explanations for Deep Neural Networks

This paper addresses formal explainability of classifying neural networks by introducing a flexible symbolic framework for an efficient, guided computation of explanations of the NN behavior, parametrized by the activations of internal neurons, and using logical engines such as SMT solvers.

Tomáš Kolárik, Faezeh Labbaf, Fabrizio Leopardi et al. · 0 citations

2026

Using Craig Interpolation for Explanation of Neural Networks (Abstract)

This work introduces space explanations, a logic-based notion of explanation that represents sufficient conditions for a neural network to predict a given class over a (potentially large and geometrically complex) subset of the feature space and demonstrates that the interpolation-based explanations are more meaningful...

Faezeh Labbaf, Tomáš Kolárik, Martin Blicha et al. · CI-BD-SOQE@FLoC · 0 citations