{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:37:45Z","timestamp":1761176265405,"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>Large language models (LLMs) have made remarkable progress in natural language processing tasks. However, efficiently integrating new knowledge and accurately answering multi-hop questions remain significant challenges. Existing methods often struggle with question semantic understanding and knowledge integration during reasoning. This paper proposes the ReAligner to address these issues. The ReAligner comprises three key components. The Multi-Representation Generator generates multiple semantically rich question representations by applying synonym replacement, syntactic variation, and semantic expansion, enhancing the model\u2019s understanding of multi-hop questions. The Knowledge Relevance Filter filters out irrelevant facts from large fact sets, improving retrieval precision and computational efficiency. The Semantic Alignment Predictor determines the most relevant fact for each sub-question by leveraging the Semantic Sharpening Unit and a trained classifier. We evaluate the ReAligner model using four datasets and compare it with state-of-the-art methods. Experimental results show that the ReAligner model outperforms existing methods.<\/jats:p>","DOI":"10.3233\/faia251295","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:57:17Z","timestamp":1761127037000},"source":"Crossref","is-referenced-by-count":0,"title":["ReAligner: Knowledge Editing via Semantic Refinement and Representation Diversification"],"prefix":"10.3233","author":[{"given":"Minghu","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer and Cyber Security, Hebei Normal University, Hebei 050024, China"},{"name":"Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Data Security, Hebei 050024, China"},{"name":"Hebei Provincial Key Laboratory of Network and Information Security, Hebei 050024, China"}]},{"given":"Shuliang","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Computer and Cyber Security, Hebei Normal University, Hebei 050024, China"},{"name":"Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Data Security, Hebei 050024, China"},{"name":"Hebei Provincial Key Laboratory of Network and Information Security, Hebei 050024, China"}]},{"given":"Yuqing","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer and Cyber Security, Hebei Normal University, Hebei 050024, China"},{"name":"Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Data Security, Hebei 050024, China"},{"name":"Hebei Provincial Key Laboratory of Network and Information Security, Hebei 050024, China"}]},{"given":"Mengjun","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Computer and Cyber Security, Hebei Normal University, Hebei 050024, China"},{"name":"Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Data Security, Hebei 050024, China"},{"name":"Hebei Provincial Key Laboratory of Network and Information Security, Hebei 050024, China"}]},{"given":"Mei","family":"He","sequence":"additional","affiliation":[{"name":"College of Computer and Cyber Security, Hebei Normal University, Hebei 050024, China"},{"name":"Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Data Security, Hebei 050024, China"},{"name":"Hebei Provincial Key Laboratory of Network and Information Security, Hebei 050024, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251295","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:57:17Z","timestamp":1761127037000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251295"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251295","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]]}}}