{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T01:43:13Z","timestamp":1787017393811,"version":"build-2736575974"},"publisher-location":"New York, NY, USA","reference-count":52,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,8,3]]},"DOI":"10.1145\/3711896.3736874","type":"proceedings-article","created":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T13:30:13Z","timestamp":1754055013000},"page":"543-554","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Causal Discovery through Synergizing Large Language Model and Data-Driven Reasoning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8393-2732","authenticated-orcid":false,"given":"Huaming","family":"Du","sequence":"first","affiliation":[{"name":"School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5225-6366","authenticated-orcid":false,"given":"Yujia","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1564-6499","authenticated-orcid":false,"given":"Baoyu","family":"Jing","sequence":"additional","affiliation":[{"name":"Siebel School of Computing and Data Science, University of Illinois, Urbana Champaign, Champaign, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8454-0025","authenticated-orcid":false,"given":"Yu","family":"Zhao","sequence":"additional","affiliation":[{"name":"Financial Intelligence and Financial Engineering Key Laboratory, Southwestern University of Finance and Economics, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9220-8647","authenticated-orcid":false,"given":"Gang","family":"Kou","sequence":"additional","affiliation":[{"name":"Xiangjiang Laboratory, Changsha, Hunan, China, Hunan University of Technology and Business, Changsha, Hunan, China, and Southwestern University of Finance and Economics, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2360-0466","authenticated-orcid":false,"given":"Guisong","family":"Liu","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Intelligent Finance, Ministry of Education, Southwestern University of Finance and Economics, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7711-1196","authenticated-orcid":false,"given":"Tao","family":"Gu","sequence":"additional","affiliation":[{"name":"Sichuan University, Chengdu, Sichuan, China and School of Business Administration, Southwestern University of Finance and Economics, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0985-0311","authenticated-orcid":false,"given":"Weimin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China"}],"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, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,8,3]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Ahmed Abdulaal Nina Montana-Brown Tiantian He Ayodeji Ijishakin Ivana Drobnjak Daniel C Castro Daniel C Alexander et al. 2023. Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata-and Data-driven Reasoning. In ICLR."},{"key":"e_1_3_2_2_2_1","first-page":"14927","article-title":"Deep evidential regression","volume":"33","author":"Amini Alexander","year":"2020","unstructured":"Alexander Amini, Wilko Schwarting, Ava Soleimany, and Daniela Rus. 2020. Deep evidential regression. In NeurIPS, Vol. 33. 14927-14937.","journal-title":"NeurIPS"},{"key":"e_1_3_2_2_3_1","volume-title":"LLM-driven Causal Discovery via Harmonized Prior. TKDE","author":"Ban Taiyu","year":"2025","unstructured":"Taiyu Ban, Lyuzhou Chen, Derui Lyu, XiangyuWang, Qinrui Zhu, and Huanhuan Chen. 2025. LLM-driven Causal Discovery via Harmonized Prior. TKDE (2025)."},{"key":"e_1_3_2_2_4_1","first-page":"13349","article-title":"Evidential deep learning for open set action recognition","author":"Bao Wentao","year":"2021","unstructured":"Wentao Bao, Qi Yu, and Yu Kong. 2021. Evidential deep learning for open set action recognition. In Proceedings of the ICCV. 13349-13358.","journal-title":"Proceedings of the ICCV."},{"key":"e_1_3_2_2_5_1","volume-title":"Yuanzhi Li, Scott Lundberg, et al.","author":"Bubeck S\u00e9bastien","year":"2023","unstructured":"S\u00e9bastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al. 2023. Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023)."},{"key":"e_1_3_2_2_6_1","first-page":"6247","article-title":"CLEAR: Can Language Models Really Understand Causal Graphs?","author":"Chen Sirui","year":"2024","unstructured":"Sirui Chen, Mengying Xu, Kun Wang, Xingyu Zeng, Rui Zhao, Shengjie Zhao, and Chaochao Lu. 2024. CLEAR: Can Language Models Really Understand Causal Graphs?. In Findings of EMNLP. 6247-6265.","journal-title":"Findings of EMNLP."},{"key":"e_1_3_2_2_7_1","first-page":"507","article-title":"Optimal structure identification with greedy search","author":"Chickering David Maxwell","year":"2002","unstructured":"David Maxwell Chickering. 2002. Optimal structure identification with greedy search. JMLR 3, Nov (2002), 507-554.","journal-title":"JMLR 3"},{"key":"e_1_3_2_2_8_1","volume-title":"Large Language Models for Constrained-Based Causal Discovery. In AAAI 2024 Workshop on''Are Large Language Models Simply Causal Parrots?''.","author":"Cohrs Kai-Hendrik","year":"2023","unstructured":"Kai-Hendrik Cohrs, Emiliano Diaz, Vasileios Sitokonstantinou, Gherardo Varando, and Gustau Camps-Valls. 2023. Large Language Models for Constrained-Based Causal Discovery. In AAAI 2024 Workshop on''Are Large Language Models Simply Causal Parrots?''."},{"key":"e_1_3_2_2_9_1","first-page":"915","article-title":"Evaluating and mitigating bias in image classifiers: A causal perspective using counterfactuals","author":"Dash Saloni","year":"2022","unstructured":"Saloni Dash, Vineeth N Balasubramanian, and Amit Sharma. 2022. Evaluating and mitigating bias in image classifiers: A causal perspective using counterfactuals. In Proceedings of the WACV. 915-924.","journal-title":"Proceedings of the WACV."},{"key":"e_1_3_2_2_10_1","volume-title":"Review of causal discovery methods based on graphical models. Frontiers in genetics 10","author":"Glymour Clark","year":"2019","unstructured":"Clark Glymour, Kun Zhang, and Peter Spirtes. 2019. Review of causal discovery methods based on graphical models. Frontiers in genetics 10 (2019), 524."},{"key":"e_1_3_2_2_11_1","first-page":"408","article-title":"Local causal discovery for estimating causal effects","author":"Gupta Shantanu","year":"2023","unstructured":"Shantanu Gupta, David Childers, and Zachary Chase Lipton. 2023. Local causal discovery for estimating causal effects. In CCLR. PMLR, 408-447.","journal-title":"CCLR. PMLR"},{"key":"e_1_3_2_2_12_1","first-page":"1","article-title":"Causal discovery from heterogeneous\/nonstationary data","volume":"21","author":"Huang Biwei","year":"2020","unstructured":"Biwei Huang, Kun Zhang, Jiji Zhang, Joseph Ramsey, Ruben Sanchez-Romero, Clark Glymour, and Bernhard Sch\u00f6lkopf. 2020. Causal discovery from heterogeneous\/nonstationary data. JMLR 21, 89 (2020), 1-53.","journal-title":"JMLR"},{"key":"e_1_3_2_2_13_1","unstructured":"Zhuo Huang Xiaobo Xia Li Shen Bo Han Mingming Gong Chen Gong and Tongliang Liu. 2023. Harnessing Out-Of-Distribution Examples via Augmenting Content and Style. In ICLR."},{"key":"e_1_3_2_2_14_1","unstructured":"Zhijing Jin Jiarui Liu Zhiheng Lyu Spencer Poff Mrinmaya Sachan Rada Mihalcea Mona Diab and Bernhard Sch\u00f6lkopf. 2023. Can Large Language Models Infer Causation from Correlation?. In ICLR."},{"key":"e_1_3_2_2_15_1","unstructured":"Zhijing Jin Jiarui Liu LYU Zhiheng Spencer Poff Mrinmaya Sachan Rada Mihalcea Mona T Diab and Bernhard Sch\u00f6lkopf. 2024. Can Large Language Models Infer Causation from Correlation?. In ICLR."},{"key":"e_1_3_2_2_16_1","first-page":"1027","article-title":"Causality-aware spatiotemporal graph neural networks for spatiotemporal time series imputation","author":"Jing Baoyu","year":"2024","unstructured":"Baoyu Jing, Dawei Zhou, Kan Ren, and Carl Yang. 2024. Causality-aware spatiotemporal graph neural networks for spatiotemporal time series imputation. In Proceedings of the CIKM. 1027-1037.","journal-title":"Proceedings of the CIKM."},{"key":"e_1_3_2_2_17_1","volume-title":"Efficient causal graph discovery using large language models. arXiv preprint arXiv:2402.01207","author":"Jiralerspong Thomas","year":"2024","unstructured":"Thomas Jiralerspong, Xiaoyin Chen, Yash More, Vedant Shah, and Yoshua Bengio. 2024. Efficient causal graph discovery using large language models. arXiv preprint arXiv:2402.01207 (2024)."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"crossref","unstructured":"Alistair EW Johnson Lucas Bulgarelli Lu Shen Alvin Gayles Ayad Shammout Steven Horng Tom J Pollard Sicheng Hao Benjamin Moody Brian Gow et al. 2023. MIMIC-IV a freely accessible electronic health record dataset. Scientific data 10 1 (2023) 1.","DOI":"10.1038\/s41597-022-01899-x"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-42337-1"},{"key":"e_1_3_2_2_20_1","volume-title":"Causal reasoning and large language models: Opening a new frontier for causality. arXiv:2305.00050","author":"Kucuman Emre","year":"2023","unstructured":"Emre Kucuman, Robert Ness, Amit Sharma, and Chenhao Tan. 2023. Causal reasoning and large language models: Opening a new frontier for causality. arXiv:2305.00050 (2023)."},{"key":"e_1_3_2_2_21_1","volume-title":"Passive learning of active causal strategies in agents and language models. NeurIPS 36","author":"Lampinen Andrew","year":"2024","unstructured":"Andrew Lampinen, Stephanie Chan, Ishita Dasgupta, Andrew Nam, and Jane Wang. 2024. Passive learning of active causal strategies in agents and language models. NeurIPS 36 (2024)."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1988.tb01721.x"},{"key":"e_1_3_2_2_23_1","unstructured":"Xiu-Chuan Li Kun Zhang and Tongliang Liu. 2023. Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions. In ICLR."},{"key":"e_1_3_2_2_24_1","unstructured":"Bingbin Liu Jordan T Ash Surbhi Goel Akshay Krishnamurthy and Cyril Zhang. 2023. Transformers Learn Shortcuts to Automata. In ICLR."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"crossref","unstructured":"Chenxi Liu Yongqiang Chen Tongliang Liu Mingming Gong James Cheng Bo Han and Kun Zhang. 2024. Discovery of the HiddenWorld with Large Language Models. In NeurIPS.","DOI":"10.52202\/079017-3249"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/jcla.22964"},{"key":"e_1_3_2_2_27_1","volume-title":"ICML 2023 Workshop on Structured Probabilistic Inference & Generative Modeling.","author":"Long Stephanie","year":"2023","unstructured":"Stephanie Long, Alexandre Pich\u00e9, Valentina Zantedeschi, Tibor Schuster, and Alexandre Drouin. 2023. Causal Discovery with Language Models as Imperfect Experts. In ICML 2023 Workshop on Structured Probabilistic Inference & Generative Modeling."},{"key":"e_1_3_2_2_28_1","volume-title":"NeurIPS 2022 Workshop on Causality for Realworld Impact.","author":"Long Stephanie","year":"2022","unstructured":"Stephanie Long, Tibor Schuster, and Alexandre Pich\u00e9. 2022. Can Large Language Models Build Causal Graphs?. In NeurIPS 2022 Workshop on Causality for Realworld Impact."},{"key":"e_1_3_2_2_29_1","first-page":"1","article-title":"Distinguishing cause from effect using observational data: methods and benchmarks","volume":"17","author":"Mooij Joris M","year":"2016","unstructured":"Joris M Mooij, Jonas Peters, Dominik Janzing, Jakob Zscheischler, and Bernhard Sch\u00f6lkopf. 2016. Distinguishing cause from effect using observational data: methods and benchmarks. JMLR 17, 32 (2016), 1-102.","journal-title":"JMLR"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0377-2217(99)00368-9"},{"key":"e_1_3_2_2_31_1","first-page":"688","article-title":"Applying large language models for causal structure learning in non small cell lung cancer","author":"Naik Narmada","year":"2024","unstructured":"Narmada Naik, Ayush Khandelwal, Mohit Joshi, Madhusudan Atre, HollisWright, Kavya Kannan, Scott Hill, Giridhar Mamidipudi, Ganapati Srinivasa, Carlo Bifulco, et al. 2024. Applying large language models for causal structure learning in non small cell lung cancer. In ICHI. 688-693.","journal-title":"ICHI."},{"key":"e_1_3_2_2_32_1","unstructured":"Kai Wang Ng Guo-Liang Tian and Man-Lai Tang. 2011. Dirichlet and related distributions: Theory methods and applications. (2011)."},{"key":"e_1_3_2_2_33_1","volume-title":"Probabilistic reasoning in intelligent systems: networks of plausible inference","author":"Pearl Judea","unstructured":"Judea Pearl. 2014. Probabilistic reasoning in intelligent systems: networks of plausible inference. Elsevier."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2670315"},{"key":"e_1_3_2_2_35_1","volume-title":"Evidential deep learning to quantify classification uncertainty. NeurIPS 31","author":"Sensoy Murat","year":"2018","unstructured":"Murat Sensoy, Lance Kaplan, and Melih Kandemir. 2018. Evidential deep learning to quantify classification uncertainty. NeurIPS 31 (2018)."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"crossref","unstructured":"Kari Sentz and Scott Ferson. 2002. Combination of evidence in Dempster-Shafer theory. Sandia National Laboratories.","DOI":"10.2172\/800792"},{"key":"e_1_3_2_2_37_1","volume-title":"Llamas KnowWhat GPTs Don't Show: Surrogate Models for Confidence Estimation. arXiv:2311.08877","author":"Shrivastava Vaishnavi","year":"2023","unstructured":"Vaishnavi Shrivastava, Percy Liang, and Ananya Kumar. 2023. Llamas KnowWhat GPTs Don't Show: Surrogate Models for Confidence Estimation. arXiv:2311.08877 (2023)."},{"key":"e_1_3_2_2_38_1","volume-title":"Bayesian analysis in expert systems. Statistical science","author":"Spiegelhalter David J","year":"1993","unstructured":"David J Spiegelhalter, A Philip Dawid, Steffen L Lauritzen, and Robert G Cowell. 1993. Bayesian analysis in expert systems. Statistical science (1993), 219-247."},{"key":"e_1_3_2_2_39_1","volume-title":"prediction, and search","author":"Spirtes Peter","unstructured":"Peter Spirtes, Clark Glymour, and Richard Scheines. 2001. Causation, prediction, and search. MIT press."},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.5555\/2074158.2074215"},{"key":"e_1_3_2_2_41_1","volume-title":"Abhinav Kumar, Saketh Bachu, Vineeth N Balasubramanian, and Amit Sharma.","author":"Vashishtha Aniket","year":"2025","unstructured":"Aniket Vashishtha, Gowtham Reddy Abbavaram, Abhinav Kumar, Saketh Bachu, Vineeth N Balasubramanian, and Amit Sharma. 2025. Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference. In ICLR."},{"key":"e_1_3_2_2_42_1","first-page":"24824","article-title":"Chain-of-thought prompting elicits reasoning in large language models","volume":"35","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022. Chain-of-thought prompting elicits reasoning in large language models. NeurIPS 35 (2022), 24824-24837.","journal-title":"NeurIPS"},{"key":"e_1_3_2_2_43_1","volume-title":"UAI 2022 Workshop on Causal Representation Learning.","author":"Willig Moritz","year":"2022","unstructured":"Moritz Willig, Matej Zecevic, Devendra Singh Dhami, and Kristian Kersting. 2022. Can Foundation Models Talk Causality?. In UAI 2022 Workshop on Causal Representation Learning."},{"key":"e_1_3_2_2_44_1","volume-title":"Devendra Singh Dhami, and Kristian Kersting","author":"Willig Moritz","year":"2023","unstructured":"Moritz Willig, Matej Zecevic, Devendra Singh Dhami, and Kristian Kersting. 2023. Probing for correlations of causal facts: Large language models and causality. preprint (2023)."},{"key":"e_1_3_2_2_45_1","volume-title":"Causality for large language models. arXiv preprint arXiv:2410.15319","author":"Wu Anpeng","year":"2024","unstructured":"Anpeng Wu, Kun Kuang, Minqin Zhu, Yingrong Wang, Yujia Zheng, Kairong Han, Baohong Li, Guangyi Chen, Fei Wu, and Kun Zhang. 2024. Causality for large language models. arXiv preprint arXiv:2410.15319 (2024)."},{"key":"e_1_3_2_2_46_1","volume-title":"Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insight. arXiv:2407.08694","author":"Xie Zhiqiang","year":"2024","unstructured":"Zhiqiang Xie, Yujia Zheng, Lizi Ottens, Kun Zhang, Christos Kozyrakis, and Jonathan Mace. 2024. Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insight. arXiv:2407.08694 (2024)."},{"key":"e_1_3_2_2_47_1","unstructured":"Miao Xiong Zhiyuan Hu Xinyang Lu YIFEI LI Jie Fu Junxian He and Bryan Hooi. 2024. Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs. In ICLR."},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-62662-3"},{"key":"e_1_3_2_2_49_1","unstructured":"Murong Yue Jie Zhao Min Zhang Liang Du and Ziyu Yao. 2023. Large Language Model Cascades with Mixture of Thought Representations for Cost-Efficient Reasoning. In ICLR."},{"key":"e_1_3_2_2_50_1","unstructured":"Cheng Zhang Stefan Bauer Paul Bennett Jiangfeng Gao Wenbo Gong Agrin Hilmkil Joel Jennings Chao Ma Tom Minka Nick Pawlowski et al. 2023. Understanding causality with large language models: Feasibility and opportunities. arXiv:2304.05524 (2023)."},{"key":"e_1_3_2_2_51_1","unstructured":"Yue Zhang Yafu Li Leyang Cui Deng Cai Lemao Liu Tingchen Fu Xinting Huang Enbo Zhao Yu Zhang Yulong Chen et al. 2023. Siren's song in the AI ocean: a survey on hallucination in large language models. arXiv:2309.01219 (2023)."},{"key":"e_1_3_2_2_52_1","first-page":"1","article-title":"Causal-learn: Causal discovery in python","volume":"25","author":"Zheng Yujia","year":"2024","unstructured":"Yujia Zheng, Biwei Huang, Wei Chen, Joseph Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, and Kun Zhang. 2024. Causal-learn: Causal discovery in python. JMLR 25, 60 (2024), 1-8.","journal-title":"JMLR"}],"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\/3711896.3736874","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T18:06:46Z","timestamp":1777572406000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3711896.3736874"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,3]]},"references-count":52,"alternative-id":["10.1145\/3711896.3736874","10.1145\/3711896"],"URL":"https:\/\/doi.org\/10.1145\/3711896.3736874","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"}}]}}