{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:09:51Z","timestamp":1750219791672,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":41,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,7,12]],"date-time":"2023-07-12T00:00:00Z","timestamp":1689120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,7,12]]},"DOI":"10.1145\/3597926.3605231","type":"proceedings-article","created":{"date-parts":[[2023,7,13]],"date-time":"2023-07-13T20:12:53Z","timestamp":1689279173000},"page":"1527-1531","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Quantitative Robustness Analysis of Neural Networks"],"prefix":"10.1145","author":[{"given":"Mara","family":"Downing","sequence":"first","affiliation":[{"name":"University of California at Santa Barbara, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,7,13]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.26226\/morressier.604907f41a80aac83ca25cda"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-44534-8_10"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/icse43902.2021.00039"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3354245"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013240"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5729"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-0348-8438-9_6"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.23919\/acc.2018.8431048"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ojcsys.2022.3187429"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/tac.2020.3046193"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/sp.2018.00058"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2338965.2336773"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-45237-7_5"},{"key":"e_1_3_2_1_14_1","unstructured":"Divya Gopinath Kaiyuan Wang Mengshi Zhang Corina S Pasareanu and Sarfraz Khurshid. 2018. Symbolic execution for deep neural networks. arXiv preprint arXiv:1807.10439. \t\t\t\t  Divya Gopinath Kaiyuan Wang Mengshi Zhang Corina S Pasareanu and Sarfraz Khurshid. 2018. Symbolic execution for deep neural networks. arXiv preprint arXiv:1807.10439."},{"key":"e_1_3_2_1_15_1","unstructured":"Yunhui Guo. 2018. A survey on methods and theories of quantized neural networks. arXiv preprint arXiv:1808.04752. \t\t\t\t  Yunhui Guo. 2018. A survey on methods and theories of quantized neural networks. arXiv preprint arXiv:1808.04752."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16496"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-63387-9_1"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2018.00286"},{"key":"e_1_3_2_1_19_1","volume-title":"Efficient exact verification of binarized neural networks. Advances in neural information processing systems, 33","author":"Jia Kai","year":"2020","unstructured":"Kai Jia and Martin Rinard . 2020. Efficient exact verification of binarized neural networks. Advances in neural information processing systems, 33 ( 2020 ), 1782\u20131795. Kai Jia and Martin Rinard. 2020. Efficient exact verification of binarized neural networks. Advances in neural information processing systems, 33 (2020), 1782\u20131795."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-63387-9_5"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-25540-4_26"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/iccv48922.2021.00773"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2019.01168"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12206"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3387939.3391594"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-14295-6_24"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3510227"},{"key":"e_1_3_2_1_28_1","unstructured":"Luiz Sena Xidan Song Erickson Alves Iury Bessa Edoardo Manino and Lucas Cordeiro. 2021. Verifying Quantized Neural Networks using SMT-Based Model Checking. arXiv preprint arXiv:2106.05997. \t\t\t\t  Luiz Sena Xidan Song Erickson Alves Iury Bessa Edoardo Manino and Lucas Cordeiro. 2021. Verifying Quantized Neural Networks using SMT-Based Model Checking. arXiv preprint arXiv:2106.05997."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/sbesc49506.2019.9046094"},{"key":"e_1_3_2_1_30_1","first-page":"6","article-title":"Fast and Effective Robustness Certification","volume":"1","author":"Singh Gagandeep","year":"2018","unstructured":"Gagandeep Singh , Timon Gehr , Matthew Mirman , Markus P\u00fcschel , and Martin T Vechev . 2018 . Fast and Effective Robustness Certification . NeurIPS , 1 , 4 (2018), 6 . Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus P\u00fcschel, and Martin T Vechev. 2018. Fast and Effective Robustness Certification. NeurIPS, 1, 4 (2018), 6.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_31_1","volume-title":"International Conference on Learning Representations.","author":"Singh Gagandeep","year":"2018","unstructured":"Gagandeep Singh , Timon Gehr , Markus P\u00fcschel , and Martin Vechev . 2018 . Boosting robustness certification of neural networks . In International Conference on Learning Representations. Gagandeep Singh, Timon Gehr, Markus P\u00fcschel, and Martin Vechev. 2018. Boosting robustness certification of neural networks. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290354"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/tevc.2019.2890858"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3238147.3238172"},{"key":"e_1_3_2_1_35_1","unstructured":"Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna Dumitru Erhan Ian Goodfellow and Rob Fergus. 2013. Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199. \t\t\t\t  Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna Dumitru Erhan Ian Goodfellow and Rob Fergus. 2013. Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Muhammad Usman Divya Gopinath and Corina S P\u0103s\u0103reanu. 2021. QuantifyML: How Good is my Machine Learning Model? arXiv preprint arXiv:2110.12588. \t\t\t\t  Muhammad Usman Divya Gopinath and Corina S P\u0103s\u0103reanu. 2021. QuantifyML: How Good is my Machine Learning Model? arXiv preprint arXiv:2110.12588.","DOI":"10.4204\/EPTCS.348.6"},{"key":"e_1_3_2_1_37_1","unstructured":"Pranshu Verma and Will Oremus. 2023. ChatGPT invented a sexual harassment scandal and named a real law prof as the accused. The Washington Post Apr https:\/\/www.washingtonpost.com\/technology\/2023\/04\/05\/chatgpt-lies\/ \t\t\t\t  Pranshu Verma and Will Oremus. 2023. ChatGPT invented a sexual harassment scandal and named a real law prof as the accused. The Washington Post Apr https:\/\/www.washingtonpost.com\/technology\/2023\/04\/05\/chatgpt-lies\/"},{"key":"e_1_3_2_1_38_1","volume-title":"Efficient formal safety analysis of neural networks. Advances in neural information processing systems, 31","author":"Wang Shiqi","year":"2018","unstructured":"Shiqi Wang , Kexin Pei , Justin Whitehouse , Junfeng Yang , and Suman Jana . 2018. Efficient formal safety analysis of neural networks. Advances in neural information processing systems, 31 ( 2018 ). Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, and Suman Jana. 2018. Efficient formal safety analysis of neural networks. Advances in neural information processing systems, 31 (2018)."},{"key":"e_1_3_2_1_39_1","volume-title":"Yee Whye Teh, and M Pawan Kumar","author":"Webb Stefan","year":"2018","unstructured":"Stefan Webb , Tom Rainforth , Yee Whye Teh, and M Pawan Kumar . 2018 . A statistical approach to assessing neural network robustness. arXiv preprint arXiv:1811.07209. Stefan Webb, Tom Rainforth, Yee Whye Teh, and M Pawan Kumar. 2018. A statistical approach to assessing neural network robustness. arXiv preprint arXiv:1811.07209."},{"key":"e_1_3_2_1_40_1","volume-title":"Efficient neural network robustness certification with general activation functions. Advances in neural information processing systems, 31","author":"Zhang Huan","year":"2018","unstructured":"Huan Zhang , Tsui-Wei Weng , Pin-Yu Chen , Cho-Jui Hsieh , and Luca Daniel . 2018. Efficient neural network robustness certification with general activation functions. Advances in neural information processing systems, 31 ( 2018 ). Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, and Luca Daniel. 2018. Efficient neural network robustness certification with general activation functions. Advances in neural information processing systems, 31 (2018)."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-81685-8_8"}],"event":{"name":"ISSTA '23: 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering","AITO"],"location":"Seattle WA USA","acronym":"ISSTA '23"},"container-title":["Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3597926.3605231","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3597926.3605231","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:59Z","timestamp":1750178279000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3597926.3605231"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,12]]},"references-count":41,"alternative-id":["10.1145\/3597926.3605231","10.1145\/3597926"],"URL":"https:\/\/doi.org\/10.1145\/3597926.3605231","relation":{},"subject":[],"published":{"date-parts":[[2023,7,12]]},"assertion":[{"value":"2023-07-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}