{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T03:00:41Z","timestamp":1776740441746,"version":"3.51.2"},"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":[[2023,8]]},"abstract":"<jats:p>We introduce DeepPSL a variant of probabilistic soft logic (PSL) to produce an end-to-end trainable system that integrates reasoning and perception. PSL represents first-order logic in terms of a convex graphical model \u2013 hinge-loss Markov random fields (HL-MRFs). PSL stands out among probabilistic logic frameworks due to its tractability having been applied to systems of more than 1 billion ground rules. The key to our approach is to represent predicates in first-order logic using deep neural networks and then to approximately back-propagate through the HL-MRF and thus train every aspect of the first-order system being represented. We believe that this approach represents an interesting direction for the integration of deep learning and reasoning techniques with applications to knowledge base learning, multi-task learning, and explainability. Evaluation on three different tasks demonstrates that DeepPSL significantly outperforms state-of-the-art neuro-symbolic methods on scalability while achieving comparable or better accuracy.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/401","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:31:30Z","timestamp":1691742690000},"page":"3606-3614","source":"Crossref","is-referenced-by-count":2,"title":["DeepPSL: End-to-End Perception and Reasoning"],"prefix":"10.24963","author":[{"given":"Sridhar","family":"Dasaratha","sequence":"first","affiliation":[{"name":"EY Global Delivery Services India LLP"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sai Akhil","family":"Puranam","sequence":"additional","affiliation":[{"name":"EY Global Delivery Services India LLP"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karmvir Singh","family":"Phogat","sequence":"additional","affiliation":[{"name":"EY Global Delivery Services India LLP"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sunil Reddy","family":"Tiyyagura","sequence":"additional","affiliation":[{"name":"EY Global Delivery Services India LLP"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nigel P.","family":"Duffy","sequence":"additional","affiliation":[{"name":"Ernst & Young (EY) LLP USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","theme":"Artificial Intelligence","location":"Macau, SAR China","acronym":"IJCAI-2023","number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2023,8,19]]},"end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:47:53Z","timestamp":1691743673000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/401"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/401","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}