{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T14:00:29Z","timestamp":1768485629899,"version":"3.49.0"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T00:00:00Z","timestamp":1695772800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T00:00:00Z","timestamp":1695772800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62007004"],"award-info":[{"award-number":["62007004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61877004"],"award-info":[{"award-number":["61877004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Beijing Natural Science Foundation","award":["4234081"],"award-info":[{"award-number":["4234081"]}]},{"name":"2021 International Chinese education research project of Center for Language Education and Cooperation of the Ministry of Education of China","award":["21YH53C"],"award-info":[{"award-number":["21YH53C"]}]},{"name":"Major Program of National Social Science Foundation of China","award":["18ZDA295"],"award-info":[{"award-number":["18ZDA295"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2024,3]]},"DOI":"10.1007\/s11227-023-05640-2","type":"journal-article","created":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T12:02:26Z","timestamp":1695816146000},"page":"5390-5407","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Enhanced cross-prompt trait scoring via syntactic feature fusion and contrastive learning"],"prefix":"10.1007","volume":"80","author":[{"given":"Jingbo","family":"Sun","sequence":"first","affiliation":[]},{"given":"Weiming","family":"Peng","sequence":"additional","affiliation":[]},{"given":"Tianbao","family":"Song","sequence":"additional","affiliation":[]},{"given":"Haitao","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Shuqin","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Jihua","family":"Song","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,27]]},"reference":[{"key":"5640_CR1","doi-asserted-by":"crossref","unstructured":"Taghipour K, Ng HT (2016) A neural approach to automated essay scoring. In: EMNLP, pp 1882\u20131891","DOI":"10.18653\/v1\/D16-1193"},{"key":"5640_CR2","doi-asserted-by":"crossref","unstructured":"Dong F, Zhang Y (2016) Automatic features for essay scoring: an empirical study. In: EMNLP, pp 1072\u20131077","DOI":"10.18653\/v1\/D16-1115"},{"key":"5640_CR3","doi-asserted-by":"crossref","unstructured":"Dong F, Zhang Y, Yang J (2017) Attention-based recurrent convolutional neural network for automatic essay scoring. In: CoNLL, pp 153\u2013162","DOI":"10.18653\/v1\/K17-1017"},{"issue":"6","key":"5640_CR4","doi-asserted-by":"publisher","first-page":"4430","DOI":"10.1007\/s11227-018-2381-y","volume":"76","author":"V Nandini","year":"2020","unstructured":"Nandini V, Uma Maheswari P (2020) Automatic assessment of descriptive answers in online examination system using semantic relational features. J Supercomput 76(6):4430\u20134448","journal-title":"J Supercomput"},{"key":"5640_CR5","doi-asserted-by":"crossref","unstructured":"Mathias S, Bhattacharyya P (2020) Can neural networks automatically score essay traits? In: BEA, pp 85\u201391","DOI":"10.18653\/v1\/2020.bea-1.8"},{"issue":"5","key":"5640_CR6","first-page":"287","volume":"11","author":"MA Hussein","year":"2020","unstructured":"Hussein MA, Hassan HA, Nassef M (2020) A trait-based deep learning automated essay scoring system with adaptive feedback. Int J Adv Comput Sci Appl 11(5):287\u2013293","journal-title":"Int J Adv Comput Sci Appl"},{"key":"5640_CR7","doi-asserted-by":"crossref","unstructured":"Jin C, He B, Hui K, Sun L (2018) Tdnn: a two-stage deep neural network for prompt-independent automated essay scoring. In: ACL, pp 1088\u20131097","DOI":"10.18653\/v1\/P18-1100"},{"key":"5640_CR8","doi-asserted-by":"crossref","unstructured":"Cao Y, Jin H, Wan X, Yu Z (2020) Domain-adaptive neural automated essay scoring. In: SIGIR, pp 1011\u20131020","DOI":"10.1145\/3397271.3401037"},{"key":"5640_CR9","unstructured":"Ridley R, He L, Dai X, Huang S, Chen J (2020) Prompt agnostic essay scorer: a domain generalization approach to cross-prompt automated essay scoring. arXiv preprint arXiv:2008.01441"},{"key":"5640_CR10","doi-asserted-by":"crossref","unstructured":"Song W, Zhang K, Fu R, Liu L, Liu T, Cheng M (2020) Multi-stage pre-training for automated chinese essay scoring. In: EMNLP, pp 6723\u20136733","DOI":"10.18653\/v1\/2020.emnlp-main.546"},{"key":"5640_CR11","doi-asserted-by":"crossref","unstructured":"Mim FS, Inoue N, Reisert P, Ouchi H, Inui K (2019) Unsupervised learning of discourse-aware text representation for essay scoring. In: ACL, pp 378\u2013385","DOI":"10.18653\/v1\/P19-2053"},{"key":"5640_CR12","doi-asserted-by":"crossref","unstructured":"Ridley R, He L, Dai X-y, Huang S, Chen J (2021) Automated cross-prompt scoring of essay traits. In: AAAI, vol. 35, pp 13745\u201313753","DOI":"10.1609\/aaai.v35i15.17620"},{"key":"5640_CR13","unstructured":"Mathias S, Bhattacharyya P (2018) Asap++: enriching the asap automated essay grading dataset with essay attribute scores. In: LREC, pp 1169\u20131173"},{"key":"5640_CR14","unstructured":"Rudner LM, Liang T (2002) Automated essay scoring using Bayes\u2019 theorem. J Technol Learn Assess 1(2)"},{"key":"5640_CR15","unstructured":"Chen H, He B (2013) Automated essay scoring by maximizing human-machine agreement. In: EMNLP, pp 1741\u20131752"},{"key":"5640_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106491","volume":"210","author":"X Li","year":"2020","unstructured":"Li X, Chen M, Nie J-Y (2020) Sednn: shared and enhanced deep neural network model for cross-prompt automated essay scoring. Knowl-Based Syst 210:106491","journal-title":"Knowl-Based Syst"},{"key":"5640_CR17","unstructured":"Chen T, Kornblith S, Norouzi M, Hinton G (2020) A simple framework for contrastive learning of visual representations. In: ICML, pp 1597\u20131607"},{"key":"5640_CR18","doi-asserted-by":"crossref","unstructured":"He K, Fan H, Wu Y, Xie S, Girshick R (2020) Momentum contrast for unsupervised visual representation learning. In: CVPR, pp 9729\u20139738","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"5640_CR19","doi-asserted-by":"crossref","unstructured":"Fang H, Wang S, Zhou M, Ding J, Xie P (2020) Cert: contrastive self-supervised learning for language understanding. arXiv preprint arXiv:2005.12766","DOI":"10.36227\/techrxiv.12308378"},{"key":"5640_CR20","doi-asserted-by":"crossref","unstructured":"Gao T, Yao X, Chen D (2021) Simcse: Simple contrastive learning of sentence embeddings. In: EMNLP, pp 6894\u20136910","DOI":"10.18653\/v1\/2021.emnlp-main.552"},{"issue":"16","key":"5640_CR21","doi-asserted-by":"publisher","first-page":"17491","DOI":"10.1007\/s11227-022-04508-1","volume":"78","author":"X Wang","year":"2022","unstructured":"Wang X, Cao Q, Wang Q, Cao Z, Zhang X, Wang P (2022) Robust log anomaly detection based on contrastive learning and multi-scale mass. J Supercomput 78(16):17491\u201317512","journal-title":"J Supercomput"},{"key":"5640_CR22","unstructured":"Logeswaran L, Lee H (2018) An efficient framework for learning sentence representations. In: ICLR"},{"key":"5640_CR23","unstructured":"Wu L, Li J, Wang Y, Meng Q, Qin T, Chen W, Zhang M, Liu T-Y, et\u00a0al. (2021) R-drop: regularized dropout for neural networks, vol 34, pp 10890\u201310905"},{"key":"5640_CR24","doi-asserted-by":"crossref","unstructured":"Shi J, Liang C, Hou L, Li J, Liu Z, Zhang H (2019) Deepchannel: salience estimation by contrastive learning for extractive document summarization. In: AAAI, vol 33, pp 6999\u20137006","DOI":"10.1609\/aaai.v33i01.33016999"},{"key":"5640_CR25","unstructured":"Meng Y, Xiong C, Bajaj P, Bennett P, Han J, Song X, et al. (2021) Coco-lm: correcting and contrasting text sequences for language model pretraining. In: NeurIPS, vol 34, pp 23102\u201323114"},{"key":"5640_CR26","doi-asserted-by":"crossref","unstructured":"Nivre J (2004) Incrementality in deterministic dependency parsing. In: Proceedings of the Workshop on Incremental Parsing: Bringing Engineering and Cognition Together, pp 50\u201357","DOI":"10.3115\/1613148.1613156"},{"key":"5640_CR27","doi-asserted-by":"crossref","unstructured":"Hadsell R, Chopra S, LeCun Y (2006) Dimensionality reduction by learning an invariant mapping. In: CVPR, vol 2, pp 1735\u20131742","DOI":"10.1109\/CVPR.2006.100"},{"key":"5640_CR28","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning CD (2014) Glove: global vectors for word representation. In: EMNLP, pp 1532\u20131543","DOI":"10.3115\/v1\/D14-1162"},{"issue":"1","key":"5640_CR29","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R (2014) Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res 15(1):1929\u20131958","journal-title":"J Mach Learn Res"},{"key":"5640_CR30","doi-asserted-by":"crossref","unstructured":"Yannakoudakis H, Cummins R (2015) Evaluating the performance of automated text scoring systems. In: BEA, pp 213\u2013223","DOI":"10.3115\/v1\/W15-0625"},{"key":"5640_CR31","doi-asserted-by":"crossref","unstructured":"Ke Z, Ng V (2019) Automated essay scoring: a survey of the state of the art. In: IJCAI, vol. 19, pp 6300\u20136308","DOI":"10.24963\/ijcai.2019\/879"},{"key":"5640_CR32","doi-asserted-by":"crossref","unstructured":"Manning CD, Surdeanu M, Bauer J, Finkel JR, Bethard S, McClosky D (2014) The stanford corenlp natural language processing toolkit. In: ACL, pp 55\u201360","DOI":"10.3115\/v1\/P14-5010"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05640-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05640-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05640-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,14]],"date-time":"2024-02-14T10:20:46Z","timestamp":1707906046000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05640-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,27]]},"references-count":32,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,3]]}},"alternative-id":["5640"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05640-2","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,27]]},"assertion":[{"value":"30 August 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 September 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"The authors declare that they have no conflicts of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The ASAP dataset that supports the findings of this study is available in .","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Availability of data and material"}}]}}