{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:38:00Z","timestamp":1761176280399,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Despite the recent success of prompt-based methods in few-shot named entity recognition (FSNER), most approaches rely on manually created prompts (e.g., templates or label words) that fail to capture sufficient semantic information. This limits generalization, particularly in cross-domain settings. Additionally, conventional FSNER methods typically assign tokens that are not meant to be recognized to a single non-entity category, even though this category encompasses both irrelevant tokens and other entities that are not needed to be recognized. Treating such a semantically diverse group as a single category introduces noise and confusion. In this paper, we propose an approach called Label-Aware Prompt learning with Non-Entity clustering Regularization for Few-Shot NER (LaPNER). We introduce a learnable prompt pool to enrich the semantic representations of label words. Additionally, we employ embedding clustering regularization to more effectively distinguish the heterogeneous tokens within the non-entity category. Comprehensive experiments on multiple benchmarks demonstrate that LaPNER consistently outperforms prior methods in various settings, highlighting its effectiveness in improving generalization across tasks.<\/jats:p>","DOI":"10.3233\/faia251346","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:58:53Z","timestamp":1761127133000},"source":"Crossref","is-referenced-by-count":0,"title":["LaPNER: Label-Aware Prompt Learning with Non-Entity Clustering Regularization for Few-Shot NER"],"prefix":"10.3233","author":[{"given":"Mark Junjie","family":"Li","sequence":"first","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China. jj.li@szu.edu.cn, zoutao2023@email.szu.edu.cn"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Zou","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China. jj.li@szu.edu.cn, zoutao2023@email.szu.edu.cn"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sunjie","family":"Huang","sequence":"additional","affiliation":[{"name":"Shenzhen Academy of Inspection and Quarantine, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yigang","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China. jj.li@szu.edu.cn, zoutao2023@email.szu.edu.cn"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qilong","family":"Gong","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China. jj.li@szu.edu.cn, zoutao2023@email.szu.edu.cn"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Li","sequence":"additional","affiliation":[{"name":"Shenzhen Academy of Inspection and Quarantine, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251346","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:58:54Z","timestamp":1761127134000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251346"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251346","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}