{"paper":{"title":"A Neurosymbolic Approach to Natural Language Formalization and Verification","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.LO"],"primary_cat":"cs.CL","authors_text":"Aditya Gokhale, Ali Torkamani, Aman Goel, Andrew M. Kent, Benjamin Kiesl-Reiter, Byron Cook, Chenyang An, Darion Cassel, Dejan Jovanovi\\'c, Dimitra Giannakopoulou, Divya Raghunathan, Duncan Clough, Ferhat Erata, Jeffrey J. Kuna, Jianan Yao, Joe Hendrix, Joseph Lilien, Marc Hudak, Michael Tautschnig, Michael W. Whalen, Nadia Labai, Nafi Diallo, Nathaniel Weir, Nick Feng, Niloofar Razavi, R\\'emi Delmas, Sam Bayless, Stefano Buliani, Victor Heorhiadi, Zvonimir Rakamari\\'c","submitted_at":"2025-11-12T06:00:37Z","abstract_excerpt":"Large Language Models perform well at natural language interpretation and reasoning, but their lack of formal correctness guarantees limits their adoption in regulated industries like finance and health-care that operate under strict policies. To address this limitation, we launched Automated Reasoning checks (ARc): a public service that (1) uses LLMs with optional human guidance to formalize natural language policies, allowing fine-grained control of the formalization process, and (2) uses inference-time autoformalization to validate logical correctness of natural language statements against "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.09008","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2511.09008/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}