{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T08:46:13Z","timestamp":1759826773980,"version":"3.44.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>Few-Shot Relation Extraction (FSRE) remains a challenging task due to the scarcity of annotated data and the limited generalization capabilities of existing models. Although large language models (LLMs) have shown potential in FSRE through in-context learning, their general-purpose training objectives often result in suboptimal performance for task-specific relation extraction. To overcome these challenges, we propose TKRE (Two-Stage Knowledge-Guided Pre-training for Relation Extraction), a novel framework that synergistically integrates LLMs with traditional relation extraction models, bridging generative and discriminative learning paradigms. TKRE introduces two key innovations: (1) leveraging LLMs to generate explanation-driven knowledge and schema-constrained synthetic data, addressing the issue of data scarcity; and (2) a two-stage pre-training strategy combining Masked Span Language Modeling (MSLM) and Span-Level Contrastive Learning (SCL) to enhance relational reasoning and generalization. Together, these components enable TKRE to effectively handle FSRE tasks. Comprehensive experiments on benchmark datasets demonstrate the efficacy of TKRE, achieving new state-of-the-art performance in FSRE and underscoring its potential for broader application in low-resource scenarios. The code and data are released on https:\/\/github.com\/UESTC-GQJ\/TKRE.<\/jats:p>","DOI":"10.24963\/ijcai.2025\/897","type":"proceedings-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:10:40Z","timestamp":1758269440000},"page":"8068-8076","source":"Crossref","is-referenced-by-count":1,"title":["Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-training"],"prefix":"10.24963","author":[{"given":"Quanjiang","family":"Guo","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China"}]},{"given":"Jinchuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China"}]},{"given":"Sijie","family":"Wang","sequence":"additional","affiliation":[{"name":"Nanyang Technological University"}]},{"given":"Ling","family":"Tian","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China"}]},{"given":"Zhao","family":"Kang","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China"}]},{"given":"Bin","family":"Yan","sequence":"additional","affiliation":[{"name":"Information Engineering University"}]},{"given":"Weidong","family":"Xiao","sequence":"additional","affiliation":[{"name":"National University of Defense Technology"}]}],"member":"10584","event":{"number":"34","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2025","name":"Thirty-Fourth International Joint Conference on Artificial Intelligence {IJCAI-25}","start":{"date-parts":[[2025,8,16]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2025,8,22]]}},"container-title":["Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T11:35:25Z","timestamp":1758627325000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2025\/897"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2025\/897","relation":{},"subject":[],"published":{"date-parts":[[2025,9]]}}}