{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T11:04:40Z","timestamp":1793444680706,"version":"4.5.0"},"reference-count":72,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12271225"],"award-info":[{"award-number":["12271225"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62006143"],"award-info":[{"award-number":["62006143"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62372180"],"award-info":[{"award-number":["62372180"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12326378"],"award-info":[{"award-number":["12326378"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11871248"],"award-info":[{"award-number":["11871248"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Emerg. Top. Comput. Intell."],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1109\/tetci.2024.3395531","type":"journal-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T13:40:58Z","timestamp":1715175658000},"page":"192-201","source":"Crossref","is-referenced-by-count":11,"title":["FeaMix: Feature Mix With Memory Batch Based on Self-Consistency Learning for Code Generation and Code Translation"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5174-5182","authenticated-orcid":false,"given":"Shuai","family":"Zhao","sequence":"first","affiliation":[{"name":"College of Information Science and Technology, Jinan University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0545-8091","authenticated-orcid":false,"given":"Jie","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Data and Computer Science, Shandong Women's University, Jinan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4494-843X","authenticated-orcid":false,"given":"Jie","family":"Fu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6757-6416","authenticated-orcid":false,"given":"Jie","family":"Chen","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Trustworthy Computing, School of Software Engineering, East China Normal University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8181-0958","authenticated-orcid":false,"given":"Jinming","family":"Wen","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Jinan University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3175605"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2019.2960546"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2022.3209394"},{"key":"ref4","article-title":"Pyramid self-attention polymerization learning for semi-supervised skeleton-based action recognition","author":"Xu","year":"2023"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3596219"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-acl.173"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.394"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.232"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3340544"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3510140"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.685"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2022.03.001"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.84"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1670"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.234"},{"key":"ref16","article-title":"Unsupervised data augmentation for consistency training","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Xie","year":"2020"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.194"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-short.97"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1561\/1500000019"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.382"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i10.21409"},{"key":"ref22","first-page":"10890","article-title":"R-drop: Regularized dropout for neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wu","year":"2021"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.552"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2023.3336920"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.538"},{"key":"ref26","article-title":"Leveraging automated unit tests for unsupervised code translation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Roziere","year":"2021"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1105"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6430"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.nlp4prog-1.7"},{"key":"ref30","article-title":"CodeGen: An open large language model for code with multi-turn program synthesis","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Nijkamp","year":"2022"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.139"},{"key":"ref32","article-title":"GraphCodeBERT: Pre-training code representations with data flow","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Guo","year":"2020"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.211"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3491101.3519665"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3520312.3534862"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3501385.3543957"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2019.2907740"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2023.3322341"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3247103"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-211229"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3222871"},{"key":"ref42","first-page":"649","article-title":"Character-level convolutional networks for text classification","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang","year":"2015"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.372"},{"key":"ref44","article-title":"Mixup: Beyond empirical risk minimization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zhang","year":"2018"},{"key":"ref45","article-title":"Augmenting data with mixup for sentence classification: An empirical study","author":"Guo","year":"2019"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.285"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11768"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548427"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i7.25971"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i10.21362"},{"key":"ref51","first-page":"103","article-title":"Wasserstein GANs with gradient penalty compute congested transport","volume-title":"Proc. Conf. Learn. Theory","author":"Milne","year":"2022"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i14.17529"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.180"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.5555\/3157096.3157329"},{"key":"ref55","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1260"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.757"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.642"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-naacl.217"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.467"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.393"},{"key":"ref62","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1145\/3196398.3196408","article-title":"Learning to mine aligned code and natural language pairs from stack overflow","volume-title":"Proc. 15th Int. Conf. Mining Softw. Repositories","author":"Yin","year":"2018"},{"key":"ref63","article-title":"CodeXGLUE: A machine learning benchmark dataset for code understanding and generation","volume-title":"Proc. 35th Conf. Neural Inf. Process. Syst. Datasets Benchmarks Track","author":"Lu","year":"2021"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.3115\/1220355.1220427"},{"key":"ref65","article-title":"CodeBLEU: A method for automatic evaluation of code synthesis","author":"Ren","year":"2020"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1186\/s44147-022-00159-4"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-short.98"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1447"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.nlp4prog-1.8"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.lifelongnlp-1.3"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.426"},{"key":"ref72","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","author":"Liu","year":"2019"}],"container-title":["IEEE Transactions on Emerging Topics in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7433297\/10850886\/10523948.pdf?arnumber=10523948","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T00:51:17Z","timestamp":1737679877000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10523948\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2]]},"references-count":72,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tetci.2024.3395531","relation":{},"ISSN":["2471-285X"],"issn-type":[{"value":"2471-285X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2]]}}}