{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:03:33Z","timestamp":1750309413316,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:00:00Z","timestamp":1729468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["62337001"],"award-info":[{"award-number":["62337001"]}]},{"name":"the Fundamental Research Funds for the Central Universities"},{"name":"the Young Scientists Fund of the Natural Science Foundation of Sichuan Province","award":["2023NSFSC1402"],"award-info":[{"award-number":["2023NSFSC1402"]}]},{"name":"the National Key Research and Development Program of China","award":["2021YFF0901000"],"award-info":[{"award-number":["2021YFF0901000"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,21]]},"DOI":"10.1145\/3627673.3679648","type":"proceedings-article","created":{"date-parts":[[2024,10,20]],"date-time":"2024-10-20T19:34:21Z","timestamp":1729452861000},"page":"768-777","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["HeckmanCD: Exploiting Selection Bias in Cognitive Diagnosis"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7889-2668","authenticated-orcid":false,"given":"Dongxuan","family":"Han","sequence":"first","affiliation":[{"name":"State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China & Southwest University of Science and Technology, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6956-5550","authenticated-orcid":false,"given":"Qi","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China & Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6196-0913","authenticated-orcid":false,"given":"Siqi","family":"Lei","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China & City University of Hong Kong, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4218-0236","authenticated-orcid":false,"given":"Shiwei","family":"Tong","sequence":"additional","affiliation":[{"name":"Tencent Company, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4817-8858","authenticated-orcid":false,"given":"Wei","family":"Huang","sequence":"additional","affiliation":[{"name":"Item Bank Department, National Education Examinations Authority, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,10,21]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Concept-aware deep knowledge tracing and exercise recommendation in an online learning system","author":"Ai Fangzhe","year":"2019","unstructured":"Fangzhe Ai, Yishuai Chen, Yuchun Guo, Yongxiang Zhao, Zhenzhu Wang, Guowei Fu, and Guangyan Wang. 2019. Concept-aware deep knowledge tracing and exercise recommendation in an online learning system. International Educational Data Mining Society (2019)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.3390\/math12010101"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3556538"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11336-009-9136-x"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-statistics-041715-033702"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939764"},{"key":"e_1_3_2_1_7_1","volume-title":"The 22nd International Conference on Artificial Intelligence and Statistics. PMLR, 1013--1021","author":"Chen Yu","year":"2019","unstructured":"Yu Chen, Telmo Silva Filho, Ricardo B Prudencio, Tom Diethe, and Peter Flach. 2019. \u03b2^3$-IRT: A New Item Response Model and its Applications. In The 22nd International Conference on Artificial Intelligence and Statistics. PMLR, 1013--1021."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1111\/bmsp.12219"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.3102\/1076998607309474"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482104"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462932"},{"key":"e_1_3_2_1_12_1","volume-title":"Bobcat: Bilevel optimization-based computerized adaptive testing. arXiv preprint arXiv:2108.07386","author":"Ghosh Aritra","year":"2021","unstructured":"Aritra Ghosh and Andrew Lan. 2021. Bobcat: Bilevel optimization-based computerized adaptive testing. arXiv preprint arXiv:2108.07386 (2021)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3010693"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.3102\/10769986013003243"},{"key":"e_1_3_2_1_15_1","volume-title":"Sample selection bias as a specification error. Econometrica: Journal of the econometric society","author":"Heckman James J","year":"1979","unstructured":"James J Heckman. 1979. Sample selection bias as a specification error. Econometrica: Journal of the econometric society (1979), 153--161."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM51629.2021.00032"},{"key":"e_1_3_2_1_17_1","volume-title":"The Eleventh International Conference on Learning Representations.","author":"Kahng Hyungu","year":"2022","unstructured":"Hyungu Kahng, Hyungrok Do, and Judy Zhong. 2022. Domain Generalization via Heckman-type Selection Models. In The Eleventh International Conference on Learning Representations."},{"key":"e_1_3_2_1_18_1","volume-title":"International conference on machine learning. PMLR","author":"Koh Pang Wei","year":"2017","unstructured":"Pang Wei Koh and Percy Liang. 2017. Understanding black-box predictions via influence functions. In International conference on machine learning. PMLR, 1885--1894."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3615455"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539486"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599429"},{"key":"e_1_3_2_1_22_1","volume-title":"A theory of test scores. Psychometric monographs","author":"Lord Frederic","year":"1952","unstructured":"Frederic Lord. 1952. A theory of test scores. Psychometric monographs (1952)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2012.656011"},{"volume-title":"Handbook of item response theory","author":"Muraki Eiji","key":"e_1_3_2_1_24_1","unstructured":"Eiji Muraki and Mari Muraki. 2016. Generalized partial credit model. In Handbook of item response theory. Chapman and Hall\/CRC, 127--137."},{"volume-title":"An introduction to copulas","author":"Nelsen Roger B","key":"e_1_3_2_1_25_1","unstructured":"Roger B Nelsen. 2006. An introduction to copulas. Springer."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40271-013-0041-0"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380255"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.publhealth.25.102802.124410"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1080\/15366367.2022.2133528"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014085"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Shiwei Tong Qi Liu Runlong Yu Wei Huang Zhenya Huang Zachary A Pardos and Weijie Jiang. 2021. Item Response Ranking for Cognitive Diagnosis.. In IJCAI. 1750--1756.","DOI":"10.24963\/ijcai.2021\/241"},{"key":"e_1_3_2_1_32_1","unstructured":"Fei Wang Weibo Gao Qi Liu Jiatong Li Guanhao Zhao Zheng Zhang Zhenya Huang Mengxiao Zhu Shijin Wang Wei Tong et al. 2024. A Survey of Models for Cognitive Diagnosis: New Developments and Future Directions. arXiv preprint arXiv:2407.05458 (2024)."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3201037"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330931"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441799"},{"volume-title":"Econometric analysis of cross section and panel data","author":"Wooldridge Jeffrey M","key":"e_1_3_2_1_36_1","unstructured":"Jeffrey M Wooldridge. 2010. Econometric analysis of cross section and panel data. MIT press."},{"key":"e_1_3_2_1_37_1","volume-title":"Variational item response theory: Fast, accurate, and expressive. arXiv preprint arXiv:2002.00276","author":"Wu Mike","year":"2020","unstructured":"Mike Wu, Richard L Davis, Benjamin W Domingue, Chris Piech, and Noah Goodman. 2020. Variational item response theory: Fast, accurate, and expressive. arXiv preprint arXiv:2002.00276 (2020)."},{"key":"e_1_3_2_1_38_1","first-page":"300","article-title":"Exploiting non-interactive exercises in cognitive diagnosis","volume":"100","author":"Yao Fangzhou","year":"2023","unstructured":"Fangzhou Yao, Qi Liu, Min Hou, Shiwei Tong, Zhenya Huang, Enhong Chen, Jing Sha, and Shijin Wang. 2023. Exploiting non-interactive exercises in cognitive diagnosis. Interaction, Vol. 100, 200 (2023), 300.","journal-title":"Interaction"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015425"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-022-3852-0"},{"key":"e_1_3_2_1_41_1","volume-title":"ME-PLAN: A deep prototypical learning with local attention network for dynamic micro-expression recognition. Neural networks","author":"Zhao Sirui","year":"2022","unstructured":"Sirui Zhao, Huaying Tang, Shifeng Liu, Yangsong Zhang, Hao Wang, Tong Xu, Enhong Chen, and Cuntai Guan. 2022. ME-PLAN: A deep prototypical learning with local attention network for dynamic micro-expression recognition. Neural networks, Vol. 153 (2022), 427--443."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.03.058"}],"event":{"name":"CIKM '24: The 33rd ACM International Conference on Information and Knowledge Management","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Boise ID USA","acronym":"CIKM '24"},"container-title":["Proceedings of the 33rd ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627673.3679648","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3627673.3679648","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:58:12Z","timestamp":1750294692000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627673.3679648"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,21]]},"references-count":42,"alternative-id":["10.1145\/3627673.3679648","10.1145\/3627673"],"URL":"https:\/\/doi.org\/10.1145\/3627673.3679648","relation":{},"subject":[],"published":{"date-parts":[[2024,10,21]]},"assertion":[{"value":"2024-10-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}