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PiShield: A NeSy Framework for Learning with Requirements

Mihaela Cătălina Stoian‚ Alex Tatomir‚ Eleonora Giunchiglia and Thomas Lukasiewicz


Deep learning models have shown their strengths in various application domains, however, they often struggle to meet safety requirements for their outputs. In this paper, we introduce PiShield, the first framework ever allowing for the integration of the requirements into the neural networks' topology. PiShield guarantees compliance with these requirements, regardless of input. Additionally, it allows for integrating requirements both at inference and/or training time, depending on the practitioners' needs. Given the widespread application of deep learning, there is a growing need for frameworks allowing for the integration of the requirements across various domains. Here, we explore three application scenarios: functional genomics, autonomous driving, and tabular data generation.

Book Title
Proceedings of the 33rd International Joint Conference on Artificial Intelligence‚ IJCAI 2024‚ Demos‚ Jeju Island‚ South Korea‚ August 3–9‚ 2024