SMiLE: Provably Enforcing Global Relational Properties in Ne…
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- DOI 10.1609/aaai.v40i44.41071
- OpenAlex ID W7139111173
- Type Conference-paper
- Language EN
- Published 14 Mar 2026
- Volume 40 (44)
- Pages 37387–37395
- Source Proceedings of the AAAI Conference on Ar…
- Publisher Association for the Advancement of …
- Countries 3
- Institutions 4
- Added 20 Mar 2026
- Updated 28 Oct 2026
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SMiLE: Provably Enforcing Global Relational Properties in Neural Networks
Conference-paper 2026 EN Diamond
Artificial Intelligence systems are increasingly deployed in settings where ensuring robustness, fairness, or domain-specific properties is essential for regulation compliance and alignment with human values. However, especially on Neural Networks, property enforcement is very challenging, and existing methods are limited to specific constraints or local properties (defined around datapoints), or…
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3 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Matteo Francobaldi | University of Bologna (IT) | |
| 2 | Michele Lombardi | University of Bologna (IT) | |
| 3 | Andrea Lodi | Technion – Israel Institute of… (IL) Cornell University (US) +1 |
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