{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T14:13:43Z","timestamp":1763302423869,"version":"3.45.0"},"publisher-location":"Singapore","reference-count":12,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819533510","type":"print"},{"value":"9789819533527","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T00:00:00Z","timestamp":1763337600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T00:00:00Z","timestamp":1763337600000},"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\/978-981-95-3352-7_26","type":"book-chapter","created":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T14:09:43Z","timestamp":1763302183000},"page":"314-324","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimizing Automated Essay On-Topic Graded Comments via\u00a0LLM-Based Prompt Augmentation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0344-9601","authenticated-orcid":false,"given":"Zhongtian","family":"Hua","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6240-0496","authenticated-orcid":false,"given":"Mengyuan","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1755-4105","authenticated-orcid":false,"given":"Meijia","family":"Yu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3238-8975","authenticated-orcid":false,"given":"Yi","family":"Luo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9402-1560","authenticated-orcid":false,"given":"Kunli","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8613-8996","authenticated-orcid":false,"given":"Yingjie","family":"Han","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,17]]},"reference":[{"key":"26_CR1","doi-asserted-by":"publisher","unstructured":"Yuan, S., He, T., Huang, H., Hou, R., Wang, M.: Automated Chinese essay scoring based on deep learning. Comput. Mater. Contin. 65(1), 817\u2013833 (2020). https:\/\/doi.org\/10.32604\/cmc.2020.010471","DOI":"10.32604\/cmc.2020.010471"},{"key":"26_CR2","unstructured":"Lin, L., Li, C.: Automated Chinese essay scoring and feedback system (2008). http:\/\/hdl.handle.net\/11536\/43549"},{"key":"26_CR3","unstructured":"Xiaohuashi: an LLM-based intelligent tutoring system for Chinese essay writing. Chinese\/English J. Educ. Measur. Eval. 4(3), 4 (2023)"},{"key":"26_CR4","unstructured":"Yang, A., Yang, B., Hui, B., et\u00a0al.: Qwen2 Technical Report arXiv preprint arXiv:2407.10671 (2024). https:\/\/arxiv.org\/abs\/2407.10671"},{"key":"26_CR5","unstructured":"DeepSeek-AI, D.G., Yang, D., et\u00a0al.: DeepSeek-R1: incentivizing reasoning capability in LLMs via Reinforcement Learning arXiv preprint arXiv:2501.12948, (2025). https:\/\/arxiv.org\/abs\/2501.12948"},{"key":"26_CR6","unstructured":"Zhang, J., et\u00a0al.: System Report for CCL24-Eval Task 7: multi-Error Modeling and fluency-targeted pre-training for Chinese essay evaluation. arXiv preprint arXiv:2407.08206 (2024). https:\/\/arxiv.org\/abs\/2407.08206"},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Kalyan, K.S.: A Survey of GPT-3 family large language models including ChatGPT and GPT-4. arXiv preprint arXiv:2310.12321 (2023). https:\/\/arxiv.org\/abs\/2310.12321","DOI":"10.2139\/ssrn.4593895"},{"key":"26_CR8","unstructured":"Wang, J., et\u00a0al.: Review of Large Vision Models and Visual Prompt Engineering. arXiv preprint arXiv:2307.00855 (2023). https:\/\/arxiv.org\/abs\/2307.00855"},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"Masikisiki, B., Marivate, V., Hlope, Y.: Investigating the efficacy of large language models in reflective assessment methods through chain of thoughts prompting arXiv preprint arXiv:2310.00272 (2023). https:\/\/arxiv.org\/abs\/2310.00272","DOI":"10.1145\/3628096.3628747"},{"key":"26_CR10","unstructured":"Chen, Y., Zhang, Y., Yu, J., Yang, L., Xia, R.: In-Context learning for knowledge base question answering for unmanned systems based on large language models. arXiv preprint arXiv:2311.02956 (2023). https:\/\/arxiv.org\/abs\/2311.02956"},{"key":"26_CR11","unstructured":"QwQ-32B: Embracing the Power of Reinforcement Learning. Qwen Team, (2025). https:\/\/qwenlm.github.io\/blog\/qwq-32b\/ Accessed 6 Mar 2025"},{"key":"26_CR12","unstructured":"NLPCC 2025 shared task 2: evaluation of essay on-topic graded comments. CUBENLP (2025). https:\/\/github.com\/cubenlp\/EOTGC-2025NLPCC Accessed 30 Apr 2025"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-3352-7_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T14:09:45Z","timestamp":1763302185000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-3352-7_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,17]]},"ISBN":["9789819533510","9789819533527"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-3352-7_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,17]]},"assertion":[{"value":"17 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLPCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF International Conference on Natural Language Processing and Chinese Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Urumqi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"7 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2025\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}