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Lang."],"published-print":{"date-parts":[[2023,6,6]]},"abstract":"<jats:p>We present Scallop, a language which combines the benefits of deep learning and logical reasoning. Scallop enables users to write a wide range of neurosymbolic applications and train them in a data- and compute-efficient manner. It achieves these goals through three key features: 1) a flexible symbolic representation that is based on the relational data model; 2) a declarative logic programming language that is based on Datalog and supports recursion, aggregation, and negation; and 3) a framework for automatic and efficient differentiable reasoning that is based on the theory of provenance semirings. We evaluate Scallop on a suite of eight neurosymbolic applications from the literature. Our evaluation demonstrates that Scallop is capable of expressing algorithmic reasoning in diverse and challenging AI tasks, provides a succinct interface for machine learning programmers to integrate logical domain knowledge, and yields solutions that are comparable or superior to state-of-the-art models in terms of accuracy. Furthermore, Scallop's solutions outperform these models in aspects such as runtime and data efficiency, interpretability, and generalizability.<\/jats:p>","DOI":"10.1145\/3591280","type":"journal-article","created":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T20:06:24Z","timestamp":1686081984000},"page":"1463-1487","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":39,"title":["Scallop: A Language for Neurosymbolic Programming"],"prefix":"10.1145","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3925-9549","authenticated-orcid":false,"given":"Ziyang","family":"Li","sequence":"first","affiliation":[{"name":"University of Pennsylvania, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3803-7995","authenticated-orcid":false,"given":"Jiani","family":"Huang","sequence":"additional","affiliation":[{"name":"University of Pennsylvania, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1348-8618","authenticated-orcid":false,"given":"Mayur","family":"Naik","sequence":"additional","affiliation":[{"name":"University of Pennsylvania, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,6,6]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. 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