{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T05:03:37Z","timestamp":1784351017545,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819233908","type":"print"},{"value":"9789819233915","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3391-5_48","type":"book-chapter","created":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T04:41:56Z","timestamp":1784349716000},"page":"583-594","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Structural Soft Prompt Injection for Large Language Models in Knowledge Graph Question Answering"],"prefix":"10.1007","author":[{"given":"Xingde","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingjuan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoming","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,19]]},"reference":[{"key":"48_CR1","first-page":"23424","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 39","author":"T Ao","year":"2025","unstructured":"Ao, T. et al.: LightPROF: a lightweight reasoning framework for large language models on knowledge graphs. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 39, pp. 23424\u201323432 (2025) https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/34510"},{"key":"48_CR2","volume-title":"International Conference on Learning Representations","author":"EJ Hu","year":"2022","unstructured":"Hu, E.J. et al.: LoRA: low-rank adaptation of large language models. In: International Conference on Learning Representations (2022) https:\/\/openreview.net\/forum?id=nZeVKeeFYf9"},{"key":"48_CR3","doi-asserted-by":"publisher","first-page":"9237","DOI":"10.18653\/v1\/2023.emnlp-main.574","volume-title":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing","author":"J Jiang","year":"2023","unstructured":"Jiang, J., Zhou, K., Dong, Z., Ye, K., Zhao, X., Wen, J.R.: StructGPT: a general framework for large language models to reason over structured data. In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 9237\u20139251. Association for Computational Linguistics, Singapore (2023). https:\/\/doi.org\/10.18653\/v1\/2023.emnlp-main.574. https:\/\/aclanthology.org\/2023.emnlp-main.574\/"},{"key":"48_CR4","volume-title":"The Eleventh International Conference on Learning Representations","author":"J Jiang","year":"2023","unstructured":"Jiang, J., Zhou, K., Zhao, X., Wen, J.R.: UniKGQA: unified retrieval and reasoning for solving multi-hop question answering over knowledge graphs. In: The Eleventh International Conference on Learning Representations (2023) https:\/\/openreview.net\/forum?id=Z63RvyAZ2Vh"},{"key":"48_CR5","first-page":"1","volume-title":"2025 IEEE International Conference on Multimedia and Expo (ICME)","author":"Z Li","year":"2025","unstructured":"Li, Z., Zhang, H., Zhang, X., Liu, C.: Enhancing anisotropy in graph neural networks with natural language semantics. In: 2025 IEEE International Conference on Multimedia and Expo (ICME), pp. 1\u201313. IEEE, Nantes, France (2025)"},{"key":"48_CR6","first-page":"371","volume-title":"Proceedings of the International Work-Conference on Artificial Neural Networks","author":"Z Liu","year":"2025","unstructured":"Liu, Z., Liang, Z., Huang, M., Li, T., Hu, Y., Zhang, X.: Multi-view cross contrastive learning for multimodal knowledge graph recommendation. In: Proceedings of the International Work-Conference on Artificial Neural Networks, pp. 371\u2013383. Springer, Cham (2025)"},{"key":"48_CR7","volume-title":"International Conference on Learning Representations","author":"L Luo","year":"2024","unstructured":"Luo, L., Li, Y.F., Haffari, G., Pan, S.: Reasoning on graphs: faithful and interpretable large language model reasoning. In: International Conference on Learning Representations (2024) https:\/\/openreview.net\/forum?id=ZGNWW7xZ6Q"},{"key":"48_CR8","doi-asserted-by":"publisher","first-page":"2447","DOI":"10.18653\/v1\/2022.findings-emnlp.181","volume-title":"Findings of the Association for Computational Linguistics: EMNLP 2022","author":"C Mavromatis","year":"2022","unstructured":"Mavromatis, C., Karypis, G.: ReaRev: adaptive reasoning for question answering over knowledge graphs. In: Findings of the Association for Computational Linguistics: EMNLP 2022, pp. 2447\u20132458. Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (2022). https:\/\/doi.org\/10.18653\/v1\/2022.findings-emnlp.181. https:\/\/aclanthology.org\/2022.findings-emnlp.181\/"},{"key":"48_CR9","doi-asserted-by":"publisher","first-page":"16682","DOI":"10.18653\/v1\/2025.findings-acl.856","volume-title":"Findings of the Association for Computational Linguistics: ACL 2025","author":"C Mavromatis","year":"2025","unstructured":"Mavromatis, C., Karypis, G.: GNN-RAG: graph neural retrieval for efficient large language model reasoning on knowledge graphs. In: Findings of the Association for Computational Linguistics: ACL 2025, pp. 16682\u201316699. Association for Computational Linguistics, Vienna, Austria (2025). https:\/\/doi.org\/10.18653\/v1\/2025.findings-acl.856"},{"issue":"12","key":"48_CR10","doi-asserted-by":"publisher","first-page":"1091","DOI":"10.16451\/j.cnki.issn1003-6059.202512003","volume":"38","author":"C Niu","year":"2025","unstructured":"Niu, C., Zhang, H., Zhang, X.: Multi-view contrastive learning for hypergraph alignment. Pattern Recognit. Artif. Intell. 38(12), 1091\u20131107 (2025). https:\/\/doi.org\/10.16451\/j.cnki.issn1003-6059.202512003","journal-title":"Pattern Recognit. Artif. Intell."},{"key":"48_CR11","doi-asserted-by":"publisher","first-page":"4498","DOI":"10.18653\/v1\/2020.acl-main.412","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Online","author":"A Saxena","year":"2020","unstructured":"Saxena, A., Tripathi, A., Talukdar, P.: Improving multi-hop question answering over knowledge graphs using knowledge base embeddings. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Online, pp. 4498\u20134507. Association for Computational Linguistics (2020). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.412"},{"key":"48_CR12","doi-asserted-by":"publisher","first-page":"4149","DOI":"10.18653\/v1\/2021.emnlp-main.341","volume-title":"Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Online","author":"J Shi","year":"2021","unstructured":"Shi, J., Cao, S., Hou, L., Li, J., Zhang, H.: Transfernet: an effective and transparent framework for multi-hop question answering over relation graph. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Online, pp. 4149\u20134158. Association for Computational Linguistics, Punta Cana, Dominican Republic (2021). https:\/\/doi.org\/10.18653\/v1\/2021.emnlp-main.341. https:\/\/aclanthology.org\/2021.emnlp-main.341\/"},{"key":"48_CR13","doi-asserted-by":"publisher","first-page":"4231","DOI":"10.18653\/v1\/D18-1455","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","author":"H Sun","year":"2018","unstructured":"Sun, H., Dhingra, B., Zaheer, M., Mazaitis, K., Salakhutdinov, R., Cohen, W.: Open domain question answering using early fusion of knowledge bases and text. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 4231\u20134242. Association for Computational Linguistics, Brussels, Belgium (2018). https:\/\/doi.org\/10.18653\/v1\/D18-1455. https:\/\/aclanthology.org\/D18-1455\/"},{"key":"48_CR14","volume-title":"The Twelfth International Conference on Learning Representations","author":"J Sun","year":"2024","unstructured":"Sun, J. et al.: Think-on-graph: deep and responsible reasoning of large language models on knowledge graphs. In: The Twelfth International Conference on Learning Representations. OpenReview.net, Vienna, Austria (2024) https:\/\/openreview.net\/forum?id=nnVO1PvbTv"},{"key":"48_CR15","doi-asserted-by":"publisher","first-page":"641","DOI":"10.18653\/v1\/N18-1059","volume-title":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)","author":"A Talmor","year":"2018","unstructured":"Talmor, A., Berant, J.: The web as a knowledge-base for answering complex questions. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 641\u2013651. Association for Computational Linguistics, New Orleans, Louisiana (2018). https:\/\/doi.org\/10.18653\/v1\/N18-1059. https:\/\/aclanthology.org\/N18-1059\/"},{"key":"48_CR16","unstructured":"Touvron, H. et al.et al.: Llama 2: open foundation and fine-tuned chat models. arXiv. (2023) https:\/\/arxiv.org\/abs\/2307.09288"},{"key":"48_CR17","doi-asserted-by":"publisher","unstructured":"Wang, K. et al.: Knowledge-driven CoT: exploring faithful reasoning in LLMs for knowledge-intensive question answering. arXiv. (2023). https:\/\/doi.org\/10.48550\/arXiv.2308.13259. https:\/\/arxiv.org\/abs\/2308.13259","DOI":"10.48550\/arXiv.2308.13259"},{"key":"48_CR18","doi-asserted-by":"publisher","first-page":"1321","DOI":"10.3115\/v1\/P15-1128","volume-title":"Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)","author":"W Yih","year":"2015","unstructured":"Yih, W., Chang, M., He, X., Gao, J.: Semantic parsing via staged query graph generation: question answering with knowledge base. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 1321\u20131331. Association for Computational Linguistics, Beijing, China (2015). https:\/\/doi.org\/10.3115\/v1\/P15-1128. https:\/\/aclanthology.org\/P15-1128\/"},{"key":"48_CR19","doi-asserted-by":"publisher","first-page":"201","DOI":"10.18653\/v1\/P16-2033","volume-title":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","author":"WT Yih","year":"2016","unstructured":"Yih, W.T., Richardson, M., Meek, C., Chang, M.W., Suh, J.: The value of semantic parse labeling for knowledge base question answering. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 201\u2013206. Association for Computational Linguistics, Berlin, Germany (2016). https:\/\/doi.org\/10.18653\/v1\/P16-2033. https:\/\/aclanthology.org\/P16-2033"},{"key":"48_CR20","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1007\/978-981-97-5618-6_29","volume-title":"Advanced Intelligent Computing Technology and Applications","author":"X Yuan","year":"2024","unstructured":"Yuan, X., Zhang, H., Li, T., Zhang, S., Zhang, X.: Multilingual knowledge graph completion with negative sample balance based adaptive self-supervised graph alignment. In: Advanced Intelligent Computing Technology and Applications, pp. 346\u2013358. Springer (2024). https:\/\/doi.org\/10.1007\/978-981-97-5618-6_29"},{"key":"48_CR21","doi-asserted-by":"publisher","first-page":"5773","DOI":"10.18653\/v1\/2022.acl-long.396","volume-title":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","author":"J Zhang","year":"2022","unstructured":"Zhang, J. et al.: Subgraph retrieval enhanced model for multi-hop knowledge base question answering. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 5773\u20135784. Association for Computational Linguistics, Dublin, Ireland (2022). https:\/\/doi.org\/10.18653\/v1\/2022.acl-long.396. https:\/\/aclanthology.org\/2022.acl-long.396\/"},{"key":"48_CR22","volume-title":"Higher-Order Relation-Enhanced Reasoning and Structural Knowledge Injection for Complex Knowledge Graph Question Answering. Master\u2019s Thesis","author":"X Zhu","year":"2026","unstructured":"Zhu, X.: Higher-Order Relation-Enhanced Reasoning and Structural Knowledge Injection for Complex Knowledge Graph Question Answering. Master\u2019s Thesis. Anhui University, Hefei, China (2026)"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3391-5_48","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T04:42:05Z","timestamp":1784349725000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3391-5_48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,19]]},"ISBN":["9789819233908","9789819233915"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3391-5_48","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,19]]},"assertion":[{"value":"19 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}