{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:35:30Z","timestamp":1783384530465,"version":"3.54.6"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>Formal verification has emerged as a powerful approach to ensure the safety and reliability of deep neural networks. However, current verification tools are limited to only a handful of properties that can be expressed as first-order constraints over the inputs and output of a network. While adversarial robustness and fairness fall under this category, many real-world properties (e.g., \"an autonomous vehicle has to stop in front of a stop sign\") remain outside the scope of existing verification technology. To mitigate this severe practical restriction, we introduce a novel framework for verifying neural networks, named neuro-symbolic verification. The key idea is to use neural networks as part of the otherwise logical specification, enabling the verification of a wide variety of complex, real-world properties, including the one above. A defining feature of our framework is that it can be implemented on top of existing verification infrastructure for neural networks, making it easily accessible to researchers and practitioners.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/503","type":"proceedings-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T02:55:56Z","timestamp":1657940156000},"page":"3622-3628","source":"Crossref","is-referenced-by-count":13,"title":["Neuro-Symbolic Verification of Deep Neural Networks"],"prefix":"10.24963","author":[{"given":"Xuan","family":"Xie","sequence":"first","affiliation":[{"name":"Max Planck Institute for Software Systems, Kaiserslautern, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristian","family":"Kersting","sequence":"additional","affiliation":[{"name":"Computer Science Department and Centre for Cognitive Science, TU Darmstadt, Germany"},{"name":"Hessian Center for AI (hessian.AI), Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Neider","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Software Systems, Kaiserslautern, Germany"},{"name":"Carl von Ossietzky University of Oldenburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","theme":"Artificial Intelligence","location":"Vienna, Austria","acronym":"IJCAI-2022","number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2022,7,23]]},"end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T11:10:04Z","timestamp":1658142604000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/503"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/503","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}