{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T14:20:54Z","timestamp":1773325254730,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":32,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819570713","type":"print"},{"value":"9789819570720","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-7072-0_35","type":"book-chapter","created":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T00:08:05Z","timestamp":1773274085000},"page":"524-540","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["TBERT: Bridging Text Generation and\u00a0Score Regression Through Hierarchical Feature Fusion Based LLM for\u00a0Automated Essay Scoring"],"prefix":"10.1007","author":[{"given":"Xia","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suiyu","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuexin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingyu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongqi","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,1]]},"reference":[{"key":"35_CR1","unstructured":"Attali, Y., Burstein, J.: Automated essay scoring with e-rater\u00ae v. 2. J. Technol. Learn. Assess. 4(3) (2006)"},{"key":"35_CR2","doi-asserted-by":"crossref","unstructured":"Bengio, Y., Louradour, J., Collobert, R., Weston, J.: Curriculum learning. In: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 41\u201348 (2009)","DOI":"10.1145\/1553374.1553380"},{"key":"35_CR3","doi-asserted-by":"crossref","unstructured":"Boquio, E.N.V., Naval,\u00a0P.C., Jr.: Beyond canonical fine-tuning: leveraging hybrid multi-layer pooled representations of BERT for automated essay scoring. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pp. 2285\u20132295 (2024)","DOI":"10.63317\/23p3293dfje5"},{"key":"35_CR4","doi-asserted-by":"crossref","unstructured":"Cao, Y., Jin, H., Wan, X., Yu, Z.: Domain-adaptive neural automated essay scoring. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1011\u20131020 (2020)","DOI":"10.1145\/3397271.3401037"},{"key":"35_CR5","doi-asserted-by":"crossref","unstructured":"Contreras, J.O., Hilles, S., Abubakar, Z.B.: Automated essay scoring with ontology based on text mining and NLTK tools. In: 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE), pp.\u00a01\u20136. IEEE (2018)","DOI":"10.1109\/ICSCEE.2018.8538399"},{"key":"35_CR6","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"566","DOI":"10.1007\/978-3-030-14118-9_57","volume-title":"The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019)","author":"SM Darwish","year":"2020","unstructured":"Darwish, S.M., Mohamed, S.K.: Automated essay evaluation based on fusion of fuzzy ontology and latent semantic analysis. In: Hassanien, A.E., Azar, A.T., Gaber, T., Bhatnagar, R., F. Tolba, M. (eds.) AMLTA 2019. AISC, vol. 921, pp. 566\u2013575. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-14118-9_57"},{"key":"35_CR7","doi-asserted-by":"crossref","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long and Short Papers), pp. 4171\u20134186 (2019)","DOI":"10.18653\/v1\/N19-1423"},{"key":"35_CR8","doi-asserted-by":"crossref","unstructured":"Do, H., Kim, Y., Lee, G.G.: Autoregressive score generation for multi-trait essay scoring. arXiv preprint arXiv:2403.08332 (2024)","DOI":"10.18653\/v1\/2024.findings-eacl.115"},{"key":"35_CR9","doi-asserted-by":"crossref","unstructured":"Dong, F., Zhang, Y., Yang, J.: Attention-based recurrent convolutional neural network for automatic essay scoring. In: Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), pp. 153\u2013162 (2017)","DOI":"10.18653\/v1\/K17-1017"},{"key":"35_CR10","unstructured":"Foltz, P.W., Laham, D., Landauer, T.K.: Automated essay scoring: applications to educational technology. In: Edmedia+ Innovate Learning, pp. 939\u2013944. Association for the Advancement of Computing in Education (AACE) (1999)"},{"key":"35_CR11","unstructured":"Hendrycks, D., Gimpel, K.: Gaussian error linear units (gelus). arXiv preprint arXiv:1606.08415 (2016)"},{"key":"35_CR12","doi-asserted-by":"crossref","unstructured":"Larkey, L.S.: Automatic essay grading using text categorization techniques. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 90\u201395 (1998)","DOI":"10.1145\/290941.290965"},{"key":"35_CR13","doi-asserted-by":"crossref","unstructured":"Lee, S., Cai, Y., Meng, D., Wang, Z., Wu, Y.: Unleashing large language models\u2019 proficiency in zero-shot essay scoring. arXiv preprint arXiv:2404.04941 (2024)","DOI":"10.18653\/v1\/2024.findings-emnlp.10"},{"issue":"11","key":"35_CR14","doi-asserted-by":"publisher","first-page":"6775","DOI":"10.3390\/app13116775","volume":"13","author":"F Li","year":"2023","unstructured":"Li, F., Xi, X., Cui, Z., Li, D., Zeng, W.: Automatic essay scoring method based on multi-scale features. Appl. Sci. 13(11), 6775 (2023)","journal-title":"Appl. Sci."},{"key":"35_CR15","doi-asserted-by":"crossref","unstructured":"Liew, P.Y., Tan, I.K.: On automated essay grading using large language models. In: Proceedings of the 2024 8th International Conference on Computer Science and Artificial Intelligence, pp. 204\u2013211 (2024)","DOI":"10.1145\/3709026.3709030"},{"issue":"9","key":"35_CR16","first-page":"1","volume":"55","author":"P Liu","year":"2023","unstructured":"Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., Neubig, G.: Pre-train, prompt, and predict: a systematic survey of prompting methods in natural language processing. ACM Comput. Surv. 55(9), 1\u201335 (2023)","journal-title":"ACM Comput. Surv."},{"key":"35_CR17","doi-asserted-by":"publisher","first-page":"86","DOI":"10.32038\/ltrq.2024.45.05","volume":"45","author":"W Liu","year":"2024","unstructured":"Liu, W.: A systematic review of automated writing evaluation feedback: validity, effects and students\u2019 engagement. Lang. Teach. Res. Q. 45, 86\u2013105 (2024)","journal-title":"Lang. Teach. Res. Q."},{"key":"35_CR18","doi-asserted-by":"crossref","unstructured":"Mansour, W., Albatarni, S., Eltanbouly, S., Elsayed, T.: Can large language models automatically score proficiency of written essays? arXiv preprint arXiv:2403.06149 (2024)","DOI":"10.63317\/45fqsdi69jq5"},{"key":"35_CR19","unstructured":"Mathias, S., Bhattacharyya, P.: Asap++: enriching the asap automated essay grading dataset with essay attribute scores. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (2018)"},{"issue":"2","key":"35_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.rmal.2023.100050","volume":"2","author":"A Mizumoto","year":"2023","unstructured":"Mizumoto, A., Eguchi, M.: Exploring the potential of using an ai language model for automated essay scoring. Res. Methods Appl. Linguist. 2(2), 100050 (2023)","journal-title":"Res. Methods Appl. Linguist."},{"key":"35_CR21","doi-asserted-by":"crossref","unstructured":"Mohler, M., Mihalcea, R.: Text-to-text semantic similarity for automatic short answer grading. In: Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009), pp. 567\u2013575 (2009)","DOI":"10.3115\/1609067.1609130"},{"key":"35_CR22","unstructured":"Page, E.B.: The imminence of... grading essays by computer. Phi Delta Kappan 47(5), 238\u2013243 (1966)"},{"key":"35_CR23","doi-asserted-by":"crossref","unstructured":"Phandi, P., Chai, K.M.A., Ng, H.T.: Flexible domain adaptation for automated essay scoring using correlated linear regression. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 431\u2013439 (2015)","DOI":"10.18653\/v1\/D15-1049"},{"key":"35_CR24","unstructured":"Radford, A., Narasimhan, K., Salimans, T., Sutskever, I., et\u00a0al.: Improving language understanding by generative pre-training (2018)"},{"issue":"140","key":"35_CR25","first-page":"1","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21(140), 1\u201367 (2020)","journal-title":"J. Mach. Learn. Res."},{"key":"35_CR26","unstructured":"Rodriguez, P.U., Jafari, A., Ormerod, C.M.: Language models and automated essay scoring. arXiv preprint arXiv:1909.09482 (2019)"},{"key":"35_CR27","unstructured":"Rudner, L.M., Liang, T.: Automated essay scoring using bayes\u2019 theorem. J. Technol. Learn. Assess. 1(2) (2002)"},{"issue":"2","key":"35_CR28","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1017\/S0958344023000265","volume":"36","author":"H Shi","year":"2024","unstructured":"Shi, H., Aryadoust, V.: A systematic review of ai-based automated written feedback research. ReCALL 36(2), 187\u2013209 (2024)","journal-title":"ReCALL"},{"key":"35_CR29","doi-asserted-by":"crossref","unstructured":"Tay, Y., Phan, M., Tuan, L.A., Hui, S.C.: Skipflow: incorporating neural coherence features for end-to-end automatic text scoring. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a032 (2018)","DOI":"10.1609\/aaai.v32i1.12045"},{"key":"35_CR30","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"35_CR31","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, C., Li, R., Lin, H.: On the use of BERT for automated essay scoring: joint learning of multi-scale essay representation. arXiv preprint arXiv:2205.03835 (2022)","DOI":"10.18653\/v1\/2022.naacl-main.249"},{"key":"35_CR32","doi-asserted-by":"crossref","unstructured":"Yang, R., Cao, J., Wen, Z., Wu, Y., He, X., et\u00a0al.: Enhancing automated essay scoring performance via fine-tuning pre-trained language models with combination of regression and ranking. Association for Computational Linguistics (ACL) (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.141"}],"container-title":["Lecture Notes in Computer Science","PRICAI 2025: Trends in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-7072-0_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T00:08:10Z","timestamp":1773274090000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-7072-0_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819570713","9789819570720"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-7072-0_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"1 April 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Wellington","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"New Zealand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pricai2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.pricai.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}