{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:03:58Z","timestamp":1750309438423,"version":"3.41.0"},"reference-count":15,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:00:00Z","timestamp":1740096000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Commun. ACM"],"published-print":{"date-parts":[[2025,3]]},"abstract":"<jats:p>After decades of promise, techniques and technologies are coming together to make artificial intelligence better at checking mathematicians\u2019 work.<\/jats:p>","DOI":"10.1145\/3703778","type":"journal-article","created":{"date-parts":[[2025,2,10]],"date-time":"2025-02-10T20:35:56Z","timestamp":1739219756000},"page":"9-11","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Feedback Loops Guide AI to Proof Checking"],"prefix":"10.1145","volume":"68","author":[{"given":"Chris","family":"Edwards","sequence":"first","affiliation":[{"name":"Surrey, Surrey, United Kingdom"}]}],"member":"320","published-online":{"date-parts":[[2025,2,21]]},"reference":[{"key":"e_1_3_1_2_1","unstructured":"Avigad J."},{"key":"e_1_3_1_3_1","unstructured":"Mathematics and the Formal Turn"},{"key":"e_1_3_1_4_1","doi-asserted-by":"crossref","unstructured":"Bulletin of the American Mathematical Society. 61 (2024) 225-240","DOI":"10.1090\/bull\/1832"},{"key":"e_1_3_1_5_1","unstructured":"Li Zhaoyu Sun J. Murphy L. Su Q. Li Zenan Zhang X. Yang K. and Si Xujie"},{"key":"e_1_3_1_6_1","unstructured":"A Survey on Deep Learning for Theorem Proving"},{"key":"e_1_3_1_7_1","unstructured":"arXiv:2404.09939 (2024)"},{"key":"e_1_3_1_8_1","unstructured":"Karatarakis M."},{"key":"e_1_3_1_9_1","unstructured":"Leveraging Large Language Models for Autoformalizing Theorems: A Case Study"},{"key":"e_1_3_1_10_1","unstructured":"Ninth Conference on Artificial Intelligence and Theorem Proving (AITP 2024)"},{"key":"e_1_3_1_11_1","unstructured":"Tarrach G. Jiang A.Q. Raggi D. Li W. and Jamnik M."},{"key":"e_1_3_1_12_1","unstructured":"More Details Please: Improving Autoformalization with More Detailed Proofs"},{"key":"e_1_3_1_13_1","unstructured":"AI for MATH Workshop at the International Conference on Machine Learning (ICML 2024)"},{"key":"e_1_3_1_14_1","unstructured":"McCarthy M."},{"key":"e_1_3_1_15_1","unstructured":"Computer programs for checking mathematical proofs"},{"key":"e_1_3_1_16_1","unstructured":"Proceedings of the Fifth Symposium in Pure Mathematics of the American Mathematical Society pages 219\u2013227 (1961)"}],"container-title":["Communications of the ACM"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3703778","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3703778","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:09:42Z","timestamp":1750295382000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3703778"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,21]]},"references-count":15,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["10.1145\/3703778"],"URL":"https:\/\/doi.org\/10.1145\/3703778","relation":{},"ISSN":["0001-0782","1557-7317"],"issn-type":[{"type":"print","value":"0001-0782"},{"type":"electronic","value":"1557-7317"}],"subject":[],"published":{"date-parts":[[2025,2,21]]},"assertion":[{"value":"2025-02-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}