{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T01:29:10Z","timestamp":1768008550309,"version":"3.49.0"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031941832","type":"print"},{"value":"9783031941849","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-94184-9_24","type":"book-chapter","created":{"date-parts":[[2025,6,7]],"date-time":"2025-06-07T16:48:20Z","timestamp":1749314900000},"page":"286-297","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Fine-Tuned LLM Method to Explore Corporate Policy-Attention Themes in the New Energy Vehicle Sector"],"prefix":"10.1007","author":[{"given":"Huiru","family":"Jia","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanfei","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiajia","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daqing","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengyuan","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhen","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,8]]},"reference":[{"key":"24_CR1","doi-asserted-by":"publisher","first-page":"1199041","DOI":"10.3389\/frsc.2023.1199041","volume":"5","author":"L Dong","year":"2023","unstructured":"Dong, L., Liu, Y.: Frontiers of policy and governance research in a smart city and artificial intelligence: an advanced review based on natural language processing. Front. Sustain. Cities. 5, 1199041 (2023)","journal-title":"Front. Sustain. Cities"},{"key":"24_CR2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.941762","volume":"13","author":"L Zhou","year":"2022","unstructured":"Zhou, L., et al.: What is policy content and how is the public's policy support? A policy cognition study based on natural language processing and social psychology. Front. Psychol. 13, 941762 (2022)","journal-title":"Front. Psychol."},{"key":"24_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.jrurstud.2024.103341","volume":"109","author":"AG Dom\u00ednguez","year":"2024","unstructured":"Dom\u00ednguez, A.G., et al.: Natural language processing of social network data for the evaluation of agricultural and rural policies. J. Rural. Stud. 109, 103341 (2024)","journal-title":"J. Rural. Stud."},{"key":"24_CR4","first-page":"3929","volume-title":"International Conference on Machine Learning","author":"K Guu","year":"2020","unstructured":"Guu, K., et al.: Retrieval augmented language model pre-training. In: International Conference on Machine Learning, pp. 3929\u20133938. PMLR (2020)"},{"issue":"2","key":"24_CR5","first-page":"3","volume":"1","author":"EJ Hu","year":"2022","unstructured":"Hu, E.J., et al.: Lora: low-rank adaptation of large language models. ICLR. 1(2), 3 (2022)","journal-title":"ICLR"},{"key":"24_CR6","first-page":"4171","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","author":"J Devlin","year":"2019","unstructured":"Devlin, J., et al.: 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, pp. 4171\u20134186 (2019)"},{"key":"24_CR7","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown, T., et al.: Language models are few-shot learners. Adv. Neural Inf. Proces. Syst. 33, 1877\u20131901 (2020)","journal-title":"Adv. Neural Inf. Proces. Syst."},{"issue":"140","key":"24_CR8","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":"24_CR9","first-page":"2307","volume-title":"Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation","author":"C Xin","year":"2024","unstructured":"Xin, C., et al.: Beyond full fine-tuning: Harnessing the power of LoRA for multi-task instruction tuning. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, pp. 2307\u20132317 (2024)"},{"key":"24_CR10","unstructured":"Houlsby, N., et al.: Parameter-efficient transfer learning for NLP. In: International Conference on Machine Learning, pp. 2790\u20132799, PMLR (2019)"},{"key":"24_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2022.112991","volume":"165","author":"M Zhao","year":"2022","unstructured":"Zhao, M., Sun, T.: Dynamic spatial spillover effect of new energy vehicle industry policies on carbon emission of transportation sector in China. Energy Policy. 165, 112991 (2022)","journal-title":"Energy Policy"},{"key":"24_CR12","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.tra.2018.02.012","volume":"110","author":"L Zhang","year":"2018","unstructured":"Zhang, L., Qin, Q.: China\u2019s new energy vehicle policies: evolution, comparison and recommendation. Transp. Res. A Policy Pract. 110, 57\u201372 (2018)","journal-title":"Transp. Res. A Policy Pract."},{"key":"24_CR13","first-page":"408","volume-title":"Proceedings of 23thWuhan International Conference on E-business","author":"Y Liu","year":"2024","unstructured":"Liu, Y., et al.: Constructing policy domain dictionary generated by DTM-embeddings to identify policy response features of listed companies in electric vehicle industry. In: Proceedings of 23thWuhan International Conference on E-business, pp. 408\u2013420. Springer (2024)"}],"container-title":["Lecture Notes in Business Information Processing","E-Business. Generative Artificial Intelligence and Management Transformation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-94184-9_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,7]],"date-time":"2025-06-07T16:48:23Z","timestamp":1749314903000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-94184-9_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031941832","9783031941849"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-94184-9_24","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"value":"1865-1348","type":"print"},{"value":"1865-1356","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"8 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WHICEB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Wuhan International Conference on E-business","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guangzhou","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":"6 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"whiceb2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/whiceb.cug.edu.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}