{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T11:26:50Z","timestamp":1780054010019,"version":"3.54.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"internal research funds from The Hong Kong Polytechnic University","award":["project no. P0036200, P0042693, P0048625, P0048752"],"award-info":[{"award-number":["project no. P0036200, P0042693, P0048625, P0048752"]}]},{"name":"Research Collaborative Project","award":["no. P0041282"],"award-info":[{"award-number":["no. P0041282"]}]},{"name":"SHTM Interdisciplinary Large Grant","award":["project no. P0043302"],"award-info":[{"award-number":["project no. P0043302"]}]},{"DOI":"10.13039\/501100006374","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["project no. 62102335"],"award-info":[{"award-number":["project no. 62102335"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"name":"General Research Funds from the Hong Kong Research Grants Council","award":["project no. PolyU 15200021, 15207322, and 15200023"],"award-info":[{"award-number":["project no. PolyU 15200021, 15207322, and 15200023"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589335.3651525","type":"proceedings-article","created":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T18:41:21Z","timestamp":1715539281000},"page":"951-954","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Interpretation-Empowered Neural Cleanse for Backdoor Attacks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6903-8996","authenticated-orcid":false,"given":"Liang-bo","family":"Ning","sequence":"first","affiliation":[{"name":"The Hong Kong Polytechnic University, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1351-476X","authenticated-orcid":false,"given":"Zeyu","family":"Dai","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9873-1770","authenticated-orcid":false,"given":"Jingran","family":"Su","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7406-5200","authenticated-orcid":false,"given":"Chao","family":"Pan","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1101-2686","authenticated-orcid":false,"given":"Luning","family":"Wang","sequence":"additional","affiliation":[{"name":"Huawei, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4049-1233","authenticated-orcid":false,"given":"Wenqi","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Computing, and Department of Management and Marketing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3370-471X","authenticated-orcid":false,"given":"Qing","family":"Li","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University, Hong Kong, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Akhilan Boopathy Sijia Liu Gaoyuan Zhang Cynthia Liu Pin-Yu Chen Shiyu Chang and Luca Daniel. 2020. Proper network interpretability helps adversarial robustness in classification. In ICML. PMLR."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.371"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359789.3359790"},{"key":"e_1_3_2_2_4_1","volume-title":"Badnets: Identifying vulnerabilities in the machine learning model supply chain. arXiv preprint arXiv:1708.06733","author":"Gu Tianyu","year":"2017","unstructured":"Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg. 2017. Badnets: Identifying vulnerabilities in the machine learning model supply chain. arXiv preprint arXiv:1708.06733 (2017)."},{"key":"e_1_3_2_2_5_1","unstructured":"Alex Krizhevsky Geoffrey Hinton et al. 2009. Learning multiple layers of features from tiny images. (2009)."},{"key":"e_1_3_2_2_6_1","volume-title":"Gradientbased learning applied to document recognition. Proc","author":"LeCun Yann","year":"1998","unstructured":"Yann LeCun, L\u00e9on Bottou, Yoshua Bengio, and Patrick Haffner. 1998. Gradientbased learning applied to document recognition. Proc. IEEE (1998)."},{"key":"e_1_3_2_2_7_1","volume-title":"Backdoor learning: A survey","author":"Li Yiming","year":"2022","unstructured":"Yiming Li, Yong Jiang, Zhifeng Li, and Shu-Tao Xia. 2022. Backdoor learning: A survey. IEEE Transactions on Neural Networks and Learning Systems (2022)."},{"key":"e_1_3_2_2_8_1","volume-title":"International Conference on Learning Representations.","author":"Li Yige","year":"2020","unstructured":"Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, and Xingjun Ma. 2020. Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_9_1","volume-title":"Trustworthy ai: A computational perspective. ACM TIST","author":"Liu Haochen","year":"2022","unstructured":"Haochen Liu, YiqiWang,Wenqi Fan, Xiaorui Liu, Yaxin Li, Shaili Jain, Yunhao Liu, Anil Jain, and Jiliang Tang. 2022. Trustworthy ai: A computational perspective. ACM TIST (2022)."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00470-5_13"},{"key":"e_1_3_2_2_11_1","volume-title":"A unified approach to interpreting model predictions. Advances in neural information processing systems 30","author":"Lundberg Scott M","year":"2017","unstructured":"Scott M Lundberg and Su-In Lee. 2017. A unified approach to interpreting model predictions. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_2_12_1","volume-title":"International conference on machine learning. 3319--3328","author":"Sundararajan Mukund","year":"2017","unstructured":"Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017. Axiomatic attribution for deep networks. In International conference on machine learning. 3319--3328."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00031"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3354209"},{"key":"e_1_3_2_2_15_1","volume-title":"Purifier: Plug-and-play Backdoor Mitigation for Pre-trained Models Via Anomaly Activation Suppression. In ACM MM.","author":"Zhang Xiaoyu","year":"2022","unstructured":"Xiaoyu Zhang, Yulin Jin, Tao Wang, Jian Lou, and Xiaofeng Chen. 2022. Purifier: Plug-and-play Backdoor Mitigation for Pre-trained Models Via Anomaly Activation Suppression. In ACM MM."},{"key":"e_1_3_2_2_16_1","volume-title":"29th {USENIX} Security Symposium ({USENIX} Security 20).","author":"Zhang Xinyang","unstructured":"Xinyang Zhang, Ningfei Wang, Hua Shen, Shouling Ji, Xiapu Luo, and Ting Wang. 2020. Interpretable deep learning under fire. In 29th {USENIX} Security Symposium ({USENIX} Security 20)."}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Companion Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3651525","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589335.3651525","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:35:10Z","timestamp":1755822910000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3651525"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":16,"alternative-id":["10.1145\/3589335.3651525","10.1145\/3589335"],"URL":"https:\/\/doi.org\/10.1145\/3589335.3651525","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}