{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:53:08Z","timestamp":1763196788818,"version":"3.45.0"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819533480","type":"print"},{"value":"9789819533497","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T00:00:00Z","timestamp":1763251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T00:00:00Z","timestamp":1763251200000},"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\/978-981-95-3349-7_45","type":"book-chapter","created":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:50:00Z","timestamp":1763196600000},"page":"588-601","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic Multi-views In-Context Learning with\u00a0Large Language Models for\u00a0Aspect-Based Sentiment Analysis"],"prefix":"10.1007","author":[{"given":"Yue","family":"Wang","sequence":"first","affiliation":[]},{"given":"Zhi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Lili","family":"Shan","sequence":"additional","affiliation":[]},{"given":"Bingquan","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,16]]},"reference":[{"key":"45_CR1","unstructured":"Achiam, J., Adler, S., Agarwal, S., et al.: GPT-4 technical report. arXiv preprint arXiv:2303.08774 (2023)"},{"key":"45_CR2","unstructured":"Brown, T.B., Mann, B., Ryder, N., et al.: Language models are few-shot learners. In: NIPS \u201920 (2020)"},{"key":"45_CR3","unstructured":"Cai, H., Song, N., Wang, Z., et al.: MEMD-ABSA: a multi-element multi-domain dataset for aspect-based sentiment analysis. arXiv preprint arXiv:2306.16956 (2023)"},{"key":"45_CR4","unstructured":"Dai, H., et al.: AugGPT: leveraging ChatGPT for text data augmentation (2023)"},{"key":"45_CR5","unstructured":"Li, X., Lv, K., Yan, H., other: Unified demonstration retriever for in-context learning. In: ACL2023, pp. 4644\u20134668 (2023)"},{"issue":"1","key":"45_CR6","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1109\/TAFFC.2021.3071388","volume":"14","author":"B Liang","year":"2023","unstructured":"Liang, B., Yin, R., Du, J., et al.: Embedding refinement framework for targeted aspect-based sentiment analysis. IEEE Trans. Affect. Comput. 14(1), 279\u2013293 (2023)","journal-title":"IEEE Trans. Affect. Comput."},{"key":"45_CR7","doi-asserted-by":"crossref","unstructured":"Liu, J., Shen, D., Zhang, Y., Dolan, B., Carin, L., Chen, W.: What makes good in-context examples for GPT-3? In: DeeLIO 2022, pp. 100\u2013114 (2022)","DOI":"10.18653\/v1\/2022.deelio-1.10"},{"key":"45_CR8","unstructured":"Liu, S., Zhou, J., Zhu, Q., et al.: Let\u2019s rectify step by step: improving aspect-based sentiment analysis with diffusion models. In: LREC-COLING 2024, pp. 10324\u201310335 (2024)"},{"key":"45_CR9","doi-asserted-by":"crossref","unstructured":"Loper, E., Bird, S.: NLTK: the natural language toolkit (2002)","DOI":"10.3115\/1118108.1118117"},{"key":"45_CR10","doi-asserted-by":"crossref","unstructured":"Peng, L., Zhang, Y., Shang, J.: Controllable data augmentation for few-shot text mining with chain-of-thought attribute manipulation. In: ACL 2024, pp. 1\u201316 (2024)","DOI":"10.18653\/v1\/2024.findings-acl.1"},{"key":"45_CR11","doi-asserted-by":"crossref","unstructured":"Pontiki, M., Galanis, D., Pavlopoulos, J., Papageorgiou, H., Androutsopoulos, I., Manandhar, S.: SemEval-2014 task 4: aspect based sentiment analysis. In: SemEval 2014, pp. 27\u201335 (2014)","DOI":"10.3115\/v1\/S14-2004"},{"issue":"4","key":"45_CR12","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1561\/1500000019","volume":"3","author":"S Robertson","year":"2009","unstructured":"Robertson, S., Zaragoza, H.: The probabilistic relevance framework: Bm25 and beyond. Found. Trends Inf. Retr. 3(4), 333\u2013389 (2009)","journal-title":"Found. Trends Inf. Retr."},{"key":"45_CR13","doi-asserted-by":"crossref","unstructured":"Rubin, O., Herzig, J., Berant, J.: Learning to retrieve prompts for in-context learning. In: ACL2022: Human Language Technologies, pp. 2655\u20132671 (2022)","DOI":"10.18653\/v1\/2022.naacl-main.191"},{"key":"45_CR14","doi-asserted-by":"crossref","unstructured":"Scaria, K., Gupta, H., Goyal, S., Sawant, S., Mishra, S., Baral, C.: InstructABSA: instruction learning for aspect based sentiment analysis. In: NAACL2024, pp. 720\u2013736 (2024)","DOI":"10.18653\/v1\/2024.naacl-short.63"},{"key":"45_CR15","doi-asserted-by":"crossref","unstructured":"Su, H., Shi, W., et al.: One embedder, any task: instruction-finetuned text embeddings. In: ACL 2023, pp. 1102\u20131121 (2023)","DOI":"10.18653\/v1\/2023.findings-acl.71"},{"key":"45_CR16","unstructured":"Touvron, H., Martin, L., Stone, K., et al.: Llama 2: open foundation and fine-tuned chat models (2023)"},{"key":"45_CR17","doi-asserted-by":"crossref","unstructured":"Wang, L., Li, L., et al.: Label words are anchors: an information flow perspective for understanding in-context learning. In: EMNLP2023. pp. 9840\u20139855 (2023)","DOI":"10.18653\/v1\/2023.emnlp-main.609"},{"key":"45_CR18","unstructured":"Wang, Q., Xu, H., Ding, K., Liang, B., Xu, R.: In-context example retrieval from multi-perspectives for few-shot aspect-based sentiment analysis. In: LREC-COLING 2024, pp. 8975\u20138985 (2024)"},{"key":"45_CR19","doi-asserted-by":"crossref","unstructured":"Wang, Y., Kordi, Y., et al.: Self-instruct: aligning language models with self-generated instructions. In: ACL2023, pp. 13484\u201313508 (2023)","DOI":"10.18653\/v1\/2023.acl-long.754"},{"key":"45_CR20","unstructured":"Wang, Z., Xie, Q., Feng, Y., Ding, Z., Yang, Z., Xia, R.: Is ChatGPT a good sentiment analyzer? In: First Conference on Language Modeling (2024)"},{"key":"45_CR21","doi-asserted-by":"crossref","unstructured":"Wang, Z., Xie, Q., Xia, R.: A simple yet effective framework for few-shot aspect-based sentiment analysis. In: SIGIR2023, pp. 1765\u20131770 (2023)","DOI":"10.1145\/3539618.3591940"},{"key":"45_CR22","unstructured":"Xu, H., Liu, B., Shu, L., Yu, P.: BERT post-training for review reading comprehension and aspect-based sentiment analysis. In: NAACL2019, pp. 2324\u20132335 (2019)"},{"key":"45_CR23","unstructured":"Yu, J., He, R., Ying, Z.: Thought propagation: an analogical approach to complex reasoning with large language models. In: ICLR2024 (2024)"},{"key":"45_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, W., Deng, Y., Li, X., Yuan, Y., Bing, L., Lam, W.: Aspect sentiment quad prediction as paraphrase generation. In: EMNLP2021, pp. 9209\u20139219 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.726"},{"key":"45_CR25","doi-asserted-by":"crossref","unstructured":"Zhou, R., Li, X., He, R., et al.: MELM: data augmentation with masked entity language modeling for low-resource NER. In: ACL2022, pp. 2251\u20132262 (2022)","DOI":"10.18653\/v1\/2022.acl-long.160"}],"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\/978-981-95-3349-7_45","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:50:06Z","timestamp":1763196606000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-3349-7_45"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,16]]},"ISBN":["9789819533480","9789819533497"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-3349-7_45","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,16]]},"assertion":[{"value":"16 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"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"}}]}}