{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T16:38:23Z","timestamp":1780418303525,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":119,"publisher":"ACM","funder":[{"DOI":"10.13039\/501100006374","name":"NIH (National Institutes of Health)","doi-asserted-by":"publisher","award":["K25DK135913"],"award-info":[{"award-number":["K25DK135913"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006374","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["2312502,2319449,2442172"],"award-info":[{"award-number":["2312502,2319449,2442172"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,8,3]]},"DOI":"10.1145\/3711896.3736556","type":"proceedings-article","created":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T20:52:41Z","timestamp":1754254361000},"page":"6195-6205","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["A Survey on Unifying Large Language Models and Knowledge Graphs for Biomedicine and Healthcare"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2189-0386","authenticated-orcid":false,"given":"Ran","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Computer Science, Emory University, Atlanta, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9925-3777","authenticated-orcid":false,"given":"Patrick","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, UIUC, Urbana, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0027-942X","authenticated-orcid":false,"given":"Linhao","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Monash University, Melbourne, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3869-6942","authenticated-orcid":false,"given":"Cao","family":"Xiao","sequence":"additional","affiliation":[{"name":"GE HealthCare, Seattle, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5866-5943","authenticated-orcid":false,"given":"Adam","family":"Cross","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, UIC, Chicago, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0794-527X","authenticated-orcid":false,"given":"Shirui","family":"Pan","sequence":"additional","affiliation":[{"name":"School of ICT, Griffith University, Brisbane, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1512-6426","authenticated-orcid":false,"given":"Jimeng","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Computer Science, UIUC, Urbana, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9145-4531","authenticated-orcid":false,"given":"Carl","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Emory University, Atlanta, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,8,3]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Yuntao Bai Saurav Kadavath Sandipan Kundu Amanda Askell Jackson Kernion Andy Jones Anna Chen Anna Goldie Azalia Mirhoseini Cameron McKinnon Carol Chen Catherine Olsson Christopher Olah Danny Hernandez Dawn Drain Deep Ganguli Dustin Li Eli Tran-Johnson Ethan Perez Jamie Kerr Jared Mueller Jeffrey Ladish Joshua Landau Kamal Ndousse Kamile Lukosuite Liane Lovitt Michael Sellitto Nelson Elhage Nicholas Schiefer Noemi Mercado Nova DasSarma Robert Lasenby Robin Larson Sam Ringer Scott Johnston Shauna Kravec Sheer El Showk Stanislav Fort Tamera Lanham Timothy Telleen-Lawton Tom Conerly Tom Henighan Tristan Hume Samuel R Bowman Zac Hatfield-Dodds Ben Mann Dario Amodei Nicholas Joseph Sam McCandlish Tom Brown and Jared Kaplan. Constitutional ai: Harmlessness from ai feedback. arXiv preprint arXiv:2212.08073 2022."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06291-2"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-022-00742-2"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-024-01083-y"},{"key":"e_1_3_2_1_5_1","volume-title":"Do large language models know about facts? arXiv preprint arXiv:2310.05177","author":"Hu Xuming","year":"2023","unstructured":"Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip S Yu, and Zhijiang Guo. Do large language models know about facts? arXiv preprint arXiv:2310.05177, 2023."},{"key":"e_1_3_2_1_6_1","volume-title":"Evaluating the logical reasoning ability of chatgpt and gpt-4. arXiv preprint arXiv:2304.03439","author":"Liu Hanmeng","year":"2023","unstructured":"Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, Jian Liu, Qiji Zhou, and Yue Zhang. Evaluating the logical reasoning ability of chatgpt and gpt-4. arXiv preprint arXiv:2304.03439, 2023."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3571730"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-023-00879-8"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447772"},{"key":"e_1_3_2_1_10_1","volume-title":"ICML 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH)","author":"Cui Hejie","year":"2023","unstructured":"Hejie Cui, Jiaying Lu, Shiyu Wang, Ran Xu, Wenjing Ma, Shaojun Yu, Yue Yu, Xuan Kan, Tianfan Fu, Chen Ling, Joyce Ho, Fei Wang, and Carl Yang. A survey on knowledge graphs for healthcare: Resources, application progress, and promise. In ICML 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH), 2023."},{"key":"e_1_3_2_1_11_1","volume-title":"Genomickb: a knowledge graph for the human genome. Nucleic Acids Research, 51(D1):D950-D956","author":"Feng Fan","year":"2023","unstructured":"Fan Feng, Feitong Tang, Yijia Gao, Dongyu Zhu, Tianjun Li, Shuyuan Yang, Yuan Yao, Yuanhao Huang, and Jie Liu. Genomickb: a knowledge graph for the human genome. Nucleic Acids Research, 51(D1):D950-D956, 2023."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/17460441.2021.1910673"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098126"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11356-023-25237-9"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-021-00519-z"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-022-01981-2"},{"key":"e_1_3_2_1_17_1","volume-title":"Transactions on Graph Data and Knowledge","author":"Pan Jeff","year":"2023","unstructured":"Jeff Pan, Simon Razniewski, Jan-Christoph Kalo, Sneha Singhania, Jiaoyan Chen, Stefan Dietze, Hajira Jabeen, Janna Omeliyanenko, Wen Zhang, Matteo Lissandrini, Russa Biswas, Gerard de Melo, Angela Bonifati, Edlira Vakaj, Mauro Dragoni, and Damien Graux. Large language models and knowledge graphs: Opportunities and challenges. Transactions on Graph Data and Knowledge, 2023."},{"key":"e_1_3_2_1_18_1","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI)","author":"He Qianyu","year":"2022","unstructured":"XintaoWang, Qianyu He, Jiaqing Liang, and Yanghua Xiao. Language models as knowledge embeddings. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2022."},{"key":"e_1_3_2_1_19_1","volume-title":"Kg-bert: Bert for knowledge graph completion. arXiv preprint arXiv:1909.03193","author":"Yao Liang","year":"2019","unstructured":"Liang Yao, Chengsheng Mao, and Yuan Luo. Kg-bert: Bert for knowledge graph completion. arXiv preprint arXiv:1909.03193, 2019."},{"key":"e_1_3_2_1_20_1","volume-title":"Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities. arXiv preprint arXiv:2305.13168","author":"Zhu Yuqi","year":"2023","unstructured":"Yuqi Zhu, XiaohanWang, Jing Chen, Shuofei Qiao, Yixin Ou, Yunzhi Yao, Shumin Deng, Huajun Chen, and Ningyu Zhang. Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities. arXiv preprint arXiv:2305.13168, 2023."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3310002"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.208"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1250"},{"key":"e_1_3_2_1_24_1","volume-title":"medikal: Integrating knowledge graphs as assistants of llms for enhanced clinical diagnosis on emrs. arXiv preprint arXiv:2406.14326","author":"Jia Mingyi","year":"2024","unstructured":"Mingyi Jia, Junwen Duan, Yan Song, and Jianxin Wang. medikal: Integrating knowledge graphs as assistants of llms for enhanced clinical diagnosis on emrs. arXiv preprint arXiv:2406.14326, 2024."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Su Chang Yu Hou Suraj Rajendran Jacqueline R M A Maasch Zehra Abedi Haotan Zhang Zilong Bai Anthony Cuturrufo Winston Guo Fayzan F Chaudhry Gregory Ghahramani Jian Tang Feixiong Cheng Yue Li Rui Zhang Jiang Bian and FeiWang. Biomedical discovery through the integrative biomedical knowledge hub (ibkh). iScience 26(4):106460 2023.","DOI":"10.1016\/j.isci.2023.106460"},{"key":"e_1_3_2_1_26_1","volume-title":"Icd- 11: an international classification of diseases for the twenty-first century. BMC Medical Informatics and Decision Making, 21:1-10","author":"Harrison James E","year":"2021","unstructured":"James E Harrison, Stefanie Weber, Robert Jakob, and Christopher G Chute. Icd- 11: an international classification of diseases for the twenty-first century. BMC Medical Informatics and Decision Making, 21:1-10, 2021."},{"key":"e_1_3_2_1_27_1","first-page":"2020","volume-title":"Filip Mundt, Lars Juhl Jensen, and Matthias Mann. Clinical knowledge graph integrates proteomics data into clinical decision-making. bioRxiv","author":"Santos Alberto","year":"2020","unstructured":"Alberto Santos, Ana R Cola\u00e7o, Annelaura B Nielsen, Lili Niu, Philipp E Geyer, Fabian Coscia, Nicolai J Wewer Albrechtsen, Filip Mundt, Lars Juhl Jensen, and Matthias Mann. Clinical knowledge graph integrates proteomics data into clinical decision-making. bioRxiv, pages 2020-05, 2020."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.1"},{"key":"e_1_3_2_1_29_1","article-title":"Guided health information seeking from llms via knowledge graph integration","author":"Yan Youfu","year":"2024","unstructured":"Youfu Yan, Yu Hou, Yongkang Xiao, Rui Zhang, and Qianwen Wang. Knownet: Guided health information seeking from llms via knowledge graph integration. IEEE Transactions on Visualization and Computer Graphics, 2024.","journal-title":"IEEE Transactions on Visualization and Computer Graphics"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591997"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657904"},{"key":"e_1_3_2_1_32_1","article-title":"fully automatic and effective knowledge graph alignment enabled by large language models","author":"Zhang Rui","year":"2023","unstructured":"Rui Zhang, Yixin Su, Bayu Distiawan Trisedya, Xiaoyan Zhao, Min Yang, Hong Cheng, and Jianzhong Qi. Autoalign: fully automatic and effective knowledge graph alignment enabled by large language models. IEEE Transactions on Knowledge and Data Engineering, 2023.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3360454"},{"key":"e_1_3_2_1_34_1","volume-title":"Simrag: Self-improving retrieval-augmented generation for adapting large language models to specialized domains. arXiv preprint arXiv:2410.17952","author":"Xu Ran","year":"2024","unstructured":"Ran Xu, Hui Liu, Sreyashi Nag, Zhenwei Dai, Yaochen Xie, Xianfeng Tang, Chen Luo, Yang Li, Joyce C Ho, Carl Yang, and Qi He. Simrag: Self-improving retrieval-augmented generation for adapting large language models to specialized domains. arXiv preprint arXiv:2410.17952, 2024."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.63317\/2i6ru3r3vfh6"},{"key":"e_1_3_2_1_36_1","first-page":"9820","volume-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)","author":"Zhang Bowen","year":"2024","unstructured":"Bowen Zhang and Harold Soh. Extract, define, canonicalize: An LLM-based framework for knowledge graph construction. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 9820-9836, 2024."},{"key":"e_1_3_2_1_37_1","first-page":"8097","article-title":"Knowledge graph efficient construction: Embedding chain-of-thought into llms","volume":"2150","author":"Nie Jixuan","year":"2024","unstructured":"Jixuan Nie, Xia Hou, Wenfeng Song, Xuan Wang, Xinyu Zhang, Xingliang Jin, Shuozhe Zhang, and Jiaqi Shi. Knowledge graph efficient construction: Embedding chain-of-thought into llms. Proceedings of the VLDB Endowment. ISSN, 2150:8097, 2024.","journal-title":"Proceedings of the VLDB Endowment. ISSN"},{"key":"e_1_3_2_1_38_1","volume-title":"Proceedings of the Conference on Neural Information Processing Systems (NeurIPS)","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, and Denny Zhou. Chain-of-thought prompting elicits reasoning in large language models. In Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2022."},{"key":"e_1_3_2_1_39_1","volume-title":"Transactions on Machine Learning Research","author":"Chen Wenhu","year":"2023","unstructured":"Wenhu Chen, Xueguang Ma, Xinyi Wang, and William W. Cohen. Program of thoughts prompting: Disentangling computation from reasoning for numerical reasoning tasks. Transactions on Machine Learning Research, 2023."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.1245"},{"key":"e_1_3_2_1_41_1","volume-title":"Codetaxo: Enhancing taxonomy expansion with limited examples via code language prompts. arXiv preprint arXiv:2408.09070","author":"Zeng Qingkai","year":"2024","unstructured":"Qingkai Zeng, Yuyang Bai, Zhaoxuan Tan, Zhenyu Wu, Shangbin Feng, and Meng Jiang. Codetaxo: Enhancing taxonomy expansion with limited examples via code language prompts. arXiv preprint arXiv:2408.09070, 2024."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3641850"},{"key":"e_1_3_2_1_43_1","volume-title":"Exploring large language models for knowledge graph completion. arXiv preprint arXiv:2308.13916","author":"Yao Liang","year":"2023","unstructured":"Liang Yao, Jiazhen Peng, Chengsheng Mao, and Yuan Luo. Exploring large language models for knowledge graph completion. arXiv preprint arXiv:2308.13916, 2023."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681327"},{"key":"e_1_3_2_1_45_1","volume-title":"The Thirty-eighth Annual Conference on Neural Information Processing Systems","author":"Guo Lingbing","year":"2024","unstructured":"Lingbing Guo, Zhongpu Bo, Zhuo Chen, Yichi Zhang, Jiaoyan Chen, Lan Yarong, Mengshu Sun, Zhiqiang Zhang, Yangyifei Luo, Qian Li, Qiang Zhang, Wen Zhang, and Huajun Chen. MKGL: Mastery of a three-word language. In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024."},{"key":"e_1_3_2_1_46_1","volume-title":"The Thirty-eighth Annual Conference on Neural Information Processing Systems","author":"Jiang Pengcheng","year":"2024","unstructured":"Pengcheng Jiang, Lang Cao, Cao Xiao, Parminder Bhatia, Jimeng Sun, and Jiawei Han. KG-FIT: Knowledge graph fine-tuning upon open-world knowledge. In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024."},{"key":"e_1_3_2_1_47_1","volume-title":"The dawn of lmms: Preliminary explorations with gpt-4v (ision). arXiv preprint arXiv:2309.17421","author":"Yang Zhengyuan","year":"2023","unstructured":"Zhengyuan Yang, Linjie Li, Kevin Lin, JianfengWang, Chung-Ching Lin, Zicheng Liu, and LijuanWang. The dawn of lmms: Preliminary explorations with gpt-4v (ision). arXiv preprint arXiv:2309.17421, 2023."},{"key":"e_1_3_2_1_48_1","volume-title":"Biomedical visual instruction tuning with clinician preference alignment. arXiv preprint arXiv:2406.13173","author":"Cui Hejie","year":"2024","unstructured":"Hejie Cui, Lingjun Mao, Xin Liang, Jieyu Zhang, Hui Ren, Quanzheng Li, Xiang Li, and Carl Yang. Biomedical visual instruction tuning with clinician preference alignment. arXiv preprint arXiv:2406.13173, 2024."},{"key":"e_1_3_2_1_49_1","volume-title":"Proceedings of the ACM International Conference on Knowledge Discovery and Data Mining (KDD)","author":"Chen Junru","year":"2022","unstructured":"Junru Chen, Yang Yang, Tao Yu, Yingying Fan, Xiaolong Mo, and Carl Yang. Brainnet: Epileptic wave detection from seeg with hierarchical graph diffusion learning. In Proceedings of the ACM International Conference on Knowledge Discovery and Data Mining (KDD), 2022."},{"key":"e_1_3_2_1_50_1","volume-title":"Proceedings of the Conference on Neural Information Processing Systems (NeurIPS)","author":"Cui Hejie","year":"2024","unstructured":"Hejie Cui, Xinyu Fang, Zihan Zhang, Ran Xu, Xuan Kan, Xin Liu, Yue Yu, Manling Li, Yangqiu Song, and Carl Yang. Open visual knowledge extraction via relation-oriented multimodality model prompting. In Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2024."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"crossref","unstructured":"Ranjay Krishna Yuke Zhu Oliver Groth Justin Johnson Kenji Hata Joshua Kravitz Stephanie Chen Yannis Kalantidis Li-Jia Li David A Shamma et al. Visual genome: Connecting language and vision using crowdsourced dense image annotations. International journal of computer vision 123:32-73 2017.","DOI":"10.1007\/s11263-016-0981-7"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.11164"},{"key":"e_1_3_2_1_53_1","volume-title":"Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Bosselut Antoine","year":"2019","unstructured":"Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi. Comet: Commonsense transformers for knowledge graph construction. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2019."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00277"},{"key":"e_1_3_2_1_55_1","volume-title":"Hierarchical knowledge graph construction from images for scalable e-commerce. arXiv preprint arXiv:2410.21237","author":"Yang Zhantao","year":"2024","unstructured":"Zhantao Yang, Han Zhang, Fangyi Chen, Anudeepsekhar Bolimera, and Marios Savvides. Hierarchical knowledge graph construction from images for scalable e-commerce. arXiv preprint arXiv:2410.21237, 2024."},{"key":"e_1_3_2_1_56_1","volume-title":"Honor Magon, Matthew P Lungren, Eric Horvitz, and Nigam H Shah. Evaluation of gpt-3.5 and gpt-4 for supporting real-world information needs in healthcare delivery. arXiv preprint arXiv:2304.13714","author":"Dash Debadutta","year":"2023","unstructured":"Debadutta Dash, Rahul Thapa, Juan M Banda, Akshay Swaminathan, Morgan Cheatham, Mehr Kashyap, Nikesh Kotecha, Jonathan H Chen, Saurabh Gombar, Lance Downing, Rachel Pedreira, Ethan Goh, Angel Arnaout, Garret Kenn Morris, Honor Magon, Matthew P Lungren, Eric Horvitz, and Nigam H Shah. Evaluation of gpt-3.5 and gpt-4 for supporting real-world information needs in healthcare delivery. arXiv preprint arXiv:2304.13714, 2023."},{"key":"e_1_3_2_1_57_1","volume-title":"Proceedings of the Conference on Neural Information Processing Systems (NeurIPS)","author":"Lewis Patrick","year":"2020","unstructured":"Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich K\u00fcttler, Mike Lewis, Wen-tau Yih, Tim Rockt\u00e4schel, Sebastian Riedel, and Douwe Kiela. Retrieval-augmented generation for knowledge-intensive nlp tasks. In Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2020."},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00280"},{"key":"e_1_3_2_1_59_1","volume-title":"Llms can't plan, but can help planning in llm-modulo frameworks. arXiv preprint arXiv:2402.01817","author":"Kambhampati Subbarao","year":"2024","unstructured":"Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, Kaya Stechly, Mudit Verma, Siddhant Bhambri, Lucas Saldyt, and Anil Murthy. Llms can't plan, but can help planning in llm-modulo frameworks. arXiv preprint arXiv:2402.01817, 2024."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.558"},{"key":"e_1_3_2_1_61_1","volume-title":"Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)","author":"Wang Lei","year":"2023","unstructured":"Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, and Ee-Peng Lim. Plan-and-solve prompting: Improving zero-shot chain-ofthought reasoning by large language models. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2023."},{"key":"e_1_3_2_1_62_1","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Yao Shunyu","year":"2022","unstructured":"Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao. React: Synergizing reasoning and acting in language models. In Proceedings of the International Conference on Learning Representations (ICLR), 2022."},{"key":"e_1_3_2_1_63_1","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Luo Linhao","year":"2024","unstructured":"Linhao Luo, Yuan-Fang Li, Reza Haf, and Shirui Pan. Reasoning on graphs: Faithful and interpretable large language model reasoning. In Proceedings of the International Conference on Learning Representations (ICLR), 2024."},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467247"},{"key":"e_1_3_2_1_65_1","volume-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)","author":"Yin Wenpeng","year":"2023","unstructured":"Wenpeng Yin, Qinyuan Ye, Pengfei Liu, Xiang Ren, and Hinrich Sch\u00fctze. Llmdriven instruction following: Progresses and concerns. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023."},{"key":"e_1_3_2_1_66_1","volume-title":"Towards faithful and robust llm specialists for evidence-based questionanswering. arXiv preprint arXiv:2402.08277","author":"Schimanski Tobias","year":"2024","unstructured":"Tobias Schimanski, Jingwei Ni, Mathias Kraus, Elliott Ash, and Markus Leippold. Towards faithful and robust llm specialists for evidence-based questionanswering. arXiv preprint arXiv:2402.08277, 2024."},{"key":"e_1_3_2_1_67_1","volume-title":"Unifying structure reasoning and language model pre-training for complex reasoning. arXiv preprint arXiv:2301.08913","author":"Wang Siyuan","year":"2023","unstructured":"Siyuan Wang, Zhongyu Wei, Jiarong Xu, Taishan Li, and Zhihao Fan. Unifying structure reasoning and language model pre-training for complex reasoning. arXiv preprint arXiv:2301.08913, 2023."},{"key":"e_1_3_2_1_68_1","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Jiang Jinhao","year":"2023","unstructured":"Jinhao Jiang, Kun Zhou, Xin Zhao, and Ji-Rong Wen. Unikgqa: Unified retrieval and reasoning for solving multi-hop question answering over knowledge graph. In Proceedings of the International Conference on Learning Representations (ICLR), 2023."},{"key":"e_1_3_2_1_69_1","volume-title":"Boosting language models reasoning with chain-of-knowledge prompting. arXiv preprint arXiv:2306.06427","author":"Wang Jianing","year":"2023","unstructured":"Jianing Wang, Qiushi Sun, Xiang Li, and Ming Gao. Boosting language models reasoning with chain-of-knowledge prompting. arXiv preprint arXiv:2306.06427, 2023."},{"key":"e_1_3_2_1_70_1","volume-title":"Knowledge-driven cot: Exploring faithful reasoning in llms for knowledge-intensive question answering. arXiv preprint arXiv:2308.13259","author":"Wang Keheng","year":"2023","unstructured":"Keheng Wang, Feiyu Duan, Sirui Wang, Peiguang Li, Yunsen Xian, Chuantao Yin, Wenge Rong, and Zhang Xiong. Knowledge-driven cot: Exploring faithful reasoning in llms for knowledge-intensive question answering. arXiv preprint arXiv:2308.13259, 2023."},{"key":"e_1_3_2_1_71_1","volume-title":"Gnn-rag: Graph neural retrieval for large language model reasoning. arXiv preprint arXiv:2405.20139","author":"Mavromatis Costas","year":"2024","unstructured":"Costas Mavromatis and George Karypis. Gnn-rag: Graph neural retrieval for large language model reasoning. arXiv preprint arXiv:2405.20139, 2024."},{"key":"e_1_3_2_1_72_1","volume-title":"Mindmap: Knowledge graph prompting sparks graph of thoughts in large language models. arXiv preprint arXiv:2308.09729","author":"Wen Yilin","year":"2023","unstructured":"Yilin Wen, Zifeng Wang, and Jimeng Sun. Mindmap: Knowledge graph prompting sparks graph of thoughts in large language models. arXiv preprint arXiv:2308.09729, 2023."},{"key":"e_1_3_2_1_73_1","volume-title":"Transactions on Machine Learning Research","author":"Huang Jin","year":"2024","unstructured":"Jin Huang, Xingjian Zhang, Qiaozhu Mei, and Jiaqi Ma. Can llms effectively leverage graph structural information through prompts, and why? Transactions on Machine Learning Research, 2024."},{"key":"e_1_3_2_1_74_1","volume-title":"Graph-constrained reasoning: Faithful reasoning on knowledge graphs with large language models. arXiv preprint arXiv:2410.13080","author":"Luo Linhao","year":"2024","unstructured":"Linhao Luo, Zicheng Zhao, Chen Gong, Gholamreza Haffari, and Shirui Pan. Graph-constrained reasoning: Faithful reasoning on knowledge graphs with large language models. arXiv preprint arXiv:2410.13080, 2024."},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1145\/367390.367400"},{"key":"e_1_3_2_1_76_1","volume-title":"Pive: Prompting with iterative verification improving graph-based generative capability of llms. arXiv preprint arXiv:2305.12392","author":"Han Jiuzhou","year":"2023","unstructured":"Jiuzhou Han, Nigel Collier,Wray Buntine, and Ehsan Shareghi. Pive: Prompting with iterative verification improving graph-based generative capability of llms. arXiv preprint arXiv:2305.12392, 2023."},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.885"},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.168"},{"key":"e_1_3_2_1_79_1","volume-title":"The Twelfth International Conference on Learning Representations","author":"Jiang Pengcheng","year":"2024","unstructured":"Pengcheng Jiang, Cao Xiao, Adam Richard Cross, and Jimeng Sun. Graphcare: Enhancing healthcare predictions with personalized knowledge graphs. In The Twelfth International Conference on Learning Representations, 2024."},{"key":"e_1_3_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.acl-short.68"},{"key":"e_1_3_2_1_81_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3679582"},{"key":"e_1_3_2_1_82_1","volume-title":"The Thirteenth International Conference on Learning Representations","author":"Jiang Pengcheng","year":"2025","unstructured":"Pengcheng Jiang, Cao Xiao, Minhao Jiang, Parminder Bhatia, Taha Kass-Hout, Jimeng Sun, and Jiawei Han. Reasoning-enhanced healthcare predictions with knowledge graph community retrieval. The Thirteenth International Conference on Learning Representations, 2025."},{"key":"e_1_3_2_1_83_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.980"},{"key":"e_1_3_2_1_84_1","volume-title":"Multimodal medical code tokenizer","author":"Su Xiaorui","year":"2025","unstructured":"Xiaorui Su, Shvat Messica, Yepeng Huang, Ruth Johnson, Lukas Fesser, Shanghua Gao, Faryad Sahneh, and Marinka Zitnik. Multimodal medical code tokenizer, 2025."},{"key":"e_1_3_2_1_85_1","volume-title":"Medrag: Enhancing retrieval-augmented generation with knowledge graph-elicited reasoning for healthcare copilot. arXiv preprint arXiv:2502.04413","author":"Zhao Xuejiao","year":"2025","unstructured":"Xuejiao Zhao, Siyan Liu, Su-Yin Yang, and Chunyan Miao. Medrag: Enhancing retrieval-augmented generation with knowledge graph-elicited reasoning for healthcare copilot. arXiv preprint arXiv:2502.04413, 2025."},{"key":"e_1_3_2_1_86_1","volume-title":"Multimodal fusion of ehr in structures and semantics: Integrating clinical records and notes with hypergraph and llm. arXiv preprint arXiv:2403.08818","author":"Cui Hejie","year":"2024","unstructured":"Hejie Cui, Xinyu Fang, Ran Xu, Xuan Kan, Joyce C Ho, and Carl Yang. Multimodal fusion of ehr in structures and semantics: Integrating clinical records and notes with hypergraph and llm. arXiv preprint arXiv:2403.08818, 2024."},{"key":"e_1_3_2_1_87_1","volume-title":"Artificial Intelligence and Data Science for Healthcare: Bridging Data-Centric AI and People-Centric Healthcare","author":"Wang Zixiang","year":"2024","unstructured":"Zixiang Wang, Yinghao Zhu, Junyi Gao, Xiaochen Zheng, Yuhui Zeng, Yifan He, Bowen Jiang, Wen Tang, Ewen M Harrison, Chengwei Pan, et al. Retcare: Towards interpretable clinical decision making through llm-driven medical knowledge retrieval. In Artificial Intelligence and Data Science for Healthcare: Bridging Data-Centric AI and People-Centric Healthcare, 2024."},{"key":"e_1_3_2_1_88_1","volume-title":"Llms-based few-shot disease predictions using ehr: A novel approach combining predictive agent reasoning and critical agent instruction. arXiv preprint arXiv:2403.15464","author":"Cui Hejie","year":"2024","unstructured":"Hejie Cui, Zhuocheng Shen, Jieyu Zhang, Hui Shao, Lianhui Qin, Joyce C Ho, and Carl Yang. Llms-based few-shot disease predictions using ehr: A novel approach combining predictive agent reasoning and critical agent instruction. arXiv preprint arXiv:2403.15464, 2024."},{"key":"e_1_3_2_1_89_1","volume-title":"ICLR2022 Machine Learning for Drug Discovery","author":"Sanchez-Fernandez Ana","year":"2022","unstructured":"Ana Sanchez-Fernandez, Elisabeth Rumetshofer, Sepp Hochreiter, and G\u00fcnter Klambauer. Contrastive learning of image-and structure-based representations in drug discovery. In ICLR2022 Machine Learning for Drug Discovery, 2022."},{"key":"e_1_3_2_1_90_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i1.32013"},{"key":"e_1_3_2_1_91_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-27137-3"},{"key":"e_1_3_2_1_92_1","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-023-00654-0"},{"key":"e_1_3_2_1_93_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-emnlp.415"},{"key":"e_1_3_2_1_94_1","first-page":"59662","article-title":"What can large language models do in chemistry? a comprehensive benchmark on eight tasks","volume":"36","author":"Guo Taicheng","year":"2023","unstructured":"Taicheng Guo, Bozhao Nan, Zhenwen Liang, Zhichun Guo, Nitesh Chawla, Olaf Wiest, Xiangliang Zhang, et al. What can large language models do in chemistry? a comprehensive benchmark on eight tasks. Advances in Neural Information Processing Systems, 36:59662-59688, 2023.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_95_1","first-page":"2024","volume-title":"Small-cohort gwas discovery with ai over massive functional genomics knowledge graph. medRxiv","author":"Huang Kexin","year":"2024","unstructured":"Kexin Huang, Tony Zeng, Soner Koc, Alexandra Pettet, Jingtian Zhou, Mika Jain, Dongbo Sun, Camilo Ruiz, Hongyu Ren, Laurence J Howe, et al. Small-cohort gwas discovery with ai over massive functional genomics knowledge graph. medRxiv, pages 2024-12, 2024."},{"key":"e_1_3_2_1_96_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-024-03233-x"},{"key":"e_1_3_2_1_97_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-42806-6"},{"key":"e_1_3_2_1_98_1","volume-title":"Language interaction network for clinical trial approval estimation. arXiv preprint arXiv:2405.06662","author":"Gao Chufan","year":"2024","unstructured":"Chufan Gao, Tianfan Fu, and Jimeng Sun. Language interaction network for clinical trial approval estimation. arXiv preprint arXiv:2405.06662, 2024."},{"key":"e_1_3_2_1_99_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-53081-z"},{"key":"e_1_3_2_1_100_1","volume-title":"Graphusion: A rag framework for knowledge graph construction with a global perspective. arXiv preprint arXiv:2410.17600","author":"Yang Rui","year":"2024","unstructured":"Rui Yang, Boming Yang, Aosong Feng, Sixun Ouyang, Moritz Blum, Tianwei She, Yuang Jiang, Freddy Lecue, Jinghui Lu, and Irene Li. Graphusion: A rag framework for knowledge graph construction with a global perspective. arXiv preprint arXiv:2410.17600, 2024."},{"key":"e_1_3_2_1_101_1","volume-title":"Biomedical knowledge graph-optimized prompt generation for large language models. Bioinformatics, 40(9):btae560","author":"Soman Karthik","year":"2024","unstructured":"Karthik Soman, Peter W Rose, John H Morris, Rabia E Akbas, Brett Smith, Braian Peetoom, Catalina Villouta-Reyes, Gabriel Cerono, Yongmei Shi, Angela Rizk-Jackson, et al. Biomedical knowledge graph-optimized prompt generation for large language models. Bioinformatics, 40(9):btae560, 2024."},{"key":"e_1_3_2_1_102_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData62323.2024.10825608"},{"key":"e_1_3_2_1_103_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics13071395"},{"key":"e_1_3_2_1_104_1","doi-asserted-by":"publisher","DOI":"10.3389\/fncom.2024.1389475"},{"key":"e_1_3_2_1_105_1","volume-title":"Autord: An automatic and end-to-end system for rare disease knowledge graph construction based on ontologiesenhanced large language models. arXiv preprint arXiv:2403.00953","author":"Cao Lang","year":"2024","unstructured":"Lang Cao, Jimeng Sun, and Adam Cross. Autord: An automatic and end-to-end system for rare disease knowledge graph construction based on ontologiesenhanced large language models. arXiv preprint arXiv:2403.00953, 2024."},{"key":"e_1_3_2_1_106_1","doi-asserted-by":"publisher","DOI":"10.2196\/46777"},{"key":"e_1_3_2_1_107_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.916"},{"key":"e_1_3_2_1_108_1","volume-title":"The Twelfth International Conference on Learning Representations","author":"Jiang Pengcheng","year":"2024","unstructured":"Pengcheng Jiang, Cao Xiao, Adam Richard Cross, and Jimeng Sun. Graphcare: Enhancing healthcare predictions with personalized knowledge graphs. In The Twelfth International Conference on Learning Representations, 2024."},{"key":"e_1_3_2_1_109_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13111858"},{"key":"e_1_3_2_1_110_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2022.104122"},{"key":"e_1_3_2_1_111_1","volume-title":"Kg4sl: knowledge graph neural network for synthetic lethality prediction in human cancers. Bioinformatics, 37(Supplement_1):i418-i425","author":"Wang Shike","year":"2021","unstructured":"Shike Wang, Fan Xu, Yunyang Li, Jie Wang, Ke Zhang, Yong Liu, Min Wu, and Jie Zheng. Kg4sl: knowledge graph neural network for synthetic lethality prediction in human cancers. Bioinformatics, 37(Supplement_1):i418-i425, 2021."},{"key":"e_1_3_2_1_112_1","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.667"},{"key":"e_1_3_2_1_113_1","doi-asserted-by":"crossref","unstructured":"Rui Yang Haoran Liu Edison Marrese-Taylor Qingcheng Zeng Yu He Ke Wanxin Li Lechao Cheng Qingyu Chen James Caverlee Yutaka Matsuo et al. Kg-rank: Enhancing large language models for medical qa with knowledge graphs and ranking techniques. arXiv preprint arXiv:2403.05881 2024.","DOI":"10.18653\/v1\/2024.bionlp-1.13"},{"key":"e_1_3_2_1_114_1","volume-title":"Question answering system based on knowledge graph in traditional chinese medicine diagnosis and treatment of viral hepatitis b. BioMed research international","author":"Yin Yating","year":"2022","unstructured":"Yating Yin, Lei Zhang, Yiguo Wang, Mingqiang Wang, Qiming Zhang, and Guozheng Li. Question answering system based on knowledge graph in traditional chinese medicine diagnosis and treatment of viral hepatitis b. BioMed research international, 2022(1):7139904, 2022."},{"key":"e_1_3_2_1_115_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2022.107220"},{"key":"e_1_3_2_1_116_1","volume-title":"Knowledge graph based agent for complex, knowledge-intensive qa in medicine. arXiv preprint arXiv:2410.04660","author":"Su Xiaorui","year":"2024","unstructured":"Xiaorui Su, Yibo Wang, Shanghua Gao, Xiaolong Liu, Valentina Giunchiglia, Djork-Arn\u00e9 Clevert, and Marinka Zitnik. Knowledge graph based agent for complex, knowledge-intensive qa in medicine. arXiv preprint arXiv:2410.04660, 2024."},{"key":"e_1_3_2_1_117_1","doi-asserted-by":"publisher","DOI":"10.2196\/17653"},{"key":"e_1_3_2_1_118_1","first-page":"879","volume-title":"Digital Personalized Health and Medicine","author":"Brisimi Theodora S","year":"2020","unstructured":"Theodora S Brisimi, Vanessa Lopez, Valentina Rho, Marco Sbodio, Gabriele Picco, Morten Kristiansen, John Segrave-Daly, and Conor Cullen. Ontologyguided policy information extraction for healthcare fraud detection. In Digital Personalized Health and Medicine, pages 879-883. IOS Press, 2020."},{"key":"e_1_3_2_1_119_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijms252111811"}],"event":{"name":"KDD '25: The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Toronto ON Canada","acronym":"KDD '25","sponsor":["SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGMOD ACM Special Interest Group on Management of Data"]},"container-title":["Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3711896.3736556","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T17:55:13Z","timestamp":1777571713000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3711896.3736556"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,3]]},"references-count":119,"alternative-id":["10.1145\/3711896.3736556","10.1145\/3711896"],"URL":"https:\/\/doi.org\/10.1145\/3711896.3736556","relation":{},"subject":[],"published":{"date-parts":[[2025,8,3]]},"assertion":[{"value":"2025-08-03","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}