{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T08:19:16Z","timestamp":1783153156227,"version":"3.54.6"},"publisher-location":"New York, NY, USA","reference-count":55,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,13]]},"DOI":"10.1145\/3774904.3792244","type":"proceedings-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T13:28:36Z","timestamp":1777296516000},"page":"3732-3743","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Traceable Latent Variable Discovery Based on Multi-Agent Collaboration"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8393-2732","authenticated-orcid":false,"given":"Huaming","family":"Du","sequence":"first","affiliation":[{"name":"Southwestern University of Finance and Economics, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7277-0175","authenticated-orcid":false,"given":"Tao","family":"Hu","sequence":"additional","affiliation":[{"name":"Southwestern University of Finance and Economics, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6947-0885","authenticated-orcid":false,"given":"Yijie","family":"Huang","sequence":"additional","affiliation":[{"name":"Southwestern University of Finance and Economics, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8454-0025","authenticated-orcid":false,"given":"Yu","family":"Zhao","sequence":"additional","affiliation":[{"name":"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":"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":"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":"Southwestern University of Finance and Economics, 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":"Emory University, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,4,12]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al.","author":"Achiam Josh","year":"2023","unstructured":"Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023. Gpt-4 technical report. arXiv:2303.08774 (2023)."},{"key":"e_1_3_2_1_2_1","first-page":"1","article-title":"Common fixed point theorems with applications to theoretical computer science","volume":"14","author":"Ahmad Jamshaid","year":"2023","unstructured":"Jamshaid Ahmad, Abdullah Eqal Al-Mazrooei, and Themistocles M Rassias. 2023. Common fixed point theorems with applications to theoretical computer science. International Journal of Nonlinear Analysis and Applications 14, 2 (2023), 1-10.","journal-title":"International Journal of Nonlinear Analysis and Applications"},{"key":"e_1_3_2_1_3_1","first-page":"10119","article-title":"Recursive causal structure learning in the presence of latent variables and selection bias","volume":"34","author":"Akbari Sina","year":"2021","unstructured":"Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, and Negar Kiyavash. 2021. Recursive causal structure learning in the presence of latent variables and selection bias. NeurIPS 34 (2021), 10119-10130.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_4_1","first-page":"249","article-title":"Learning linear bayesian networks with latent variables","author":"Anandkumar Animashree","year":"2013","unstructured":"Animashree Anandkumar, Daniel Hsu, Adel Javanmard, and Sham Kakade. 2013. Learning linear bayesian networks with latent variables. In ICML. 249-257.","journal-title":"ICML."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Barbara M Byrne. 2013. Structural equation modeling with Mplus: Basic concepts applications and programming. routledge.","DOI":"10.4324\/9780203807644"},{"key":"e_1_3_2_1_6_1","unstructured":"Mert Cemri Melissa Z Pan Shuyi Yang Lakshya A Agrawal Bhavya Chopra Rishabh Tiwari Kurt Keutzer Aditya Parameswaran Dan Klein Kannan Ramchandran et al. 2025. Why do multi-agent llm systems fail? arXiv preprint arXiv:2503.13657 (2025)."},{"key":"e_1_3_2_1_7_1","volume-title":"ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs. In ACL. 7066-7085","author":"Chen Justin","year":"2024","unstructured":"Justin Chen, Swarnadeep Saha, and Mohit Bansal. 2024. ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs. In ACL. 7066-7085."},{"key":"e_1_3_2_1_8_1","first-page":"4850","article-title":"RareBench: can LLMs serve as rare diseases specialists?","author":"Chen Xuanzhong","year":"2024","unstructured":"Xuanzhong Chen, Xiaohao Mao, Qihan Guo, Lun Wang, Shuyang Zhang, and Ting Chen. 2024. RareBench: can LLMs serve as rare diseases specialists?. In KDD. 4850-4861.","journal-title":"KDD."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i6.20585"},{"key":"e_1_3_2_1_10_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. Journal of machine learning research 3, Nov (2002), 507-554.","journal-title":"Journal of machine learning research 3"},{"key":"e_1_3_2_1_11_1","unstructured":"Xinshuai Dong Biwei Huang Ignavier Ng Xiangchen Song Yujia Zheng Songyao Jin Roberto Legaspi Peter Spirtes and Kun Zhang. 2024. A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. In ICLR."},{"key":"e_1_3_2_1_12_1","first-page":"543","article-title":"Causal Discovery through Synergizing Large Language Model and Data-Driven Reasoning","author":"Du Huaming","year":"2025","unstructured":"Huaming Du, Yujia Zheng, Baoyu Jing, Yu Zhao, Gang Kou, Guisong Liu, Tao Gu, Weimin Li, and Carl Yang. 2025. Causal Discovery through Synergizing Large Language Model and Data-Driven Reasoning. In KDD. 543-554.","journal-title":"KDD."},{"key":"e_1_3_2_1_13_1","unstructured":"Yilun Du Shuang Li Antonio Torralba Joshua B Tenenbaum and Igor Mordatch. 2024. Improving factuality and reasoning in language models through multiagent debate. In ICML."},{"key":"e_1_3_2_1_14_1","volume-title":"Theory of mind. Current biology 15, 17","author":"Frith Chris","year":"2005","unstructured":"Chris Frith and Uta Frith. 2005. Theory of mind. Current biology 15, 17 (2005), R644-R645."},{"key":"e_1_3_2_1_15_1","first-page":"1587","article-title":"Addressing function approximation error in actor-critic methods","author":"Fujimoto Scott","year":"2018","unstructured":"Scott Fujimoto, Herke Hoof, and David Meger. 2018. Addressing function approximation error in actor-critic methods. In ICML. PMLR, 1587-1596.","journal-title":"ICML. PMLR"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-025-09422-z"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1038\/s43588-023-00527-x"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Elad Hazan et al. 2016. Introduction to online convex optimization. Foundations and Trends\u00ae in Optimization 2 3-4 (2016) 157-325.","DOI":"10.1561\/2400000013"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cognition.2019.04.010"},{"key":"e_1_3_2_1_20_1","volume-title":"Zijuan Lin, et al.","author":"Hong Sirui","year":"2024","unstructured":"Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Ceyao Zhang, Jinlin Wang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, et al. 2024. MetaGPT: Meta programming for a multi-agent collaborative framework. In ICLR."},{"key":"e_1_3_2_1_21_1","volume-title":"Feng Xie, Clark Glymour, and Kun Zhang.","author":"Huang Biwei","year":"2022","unstructured":"Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, and Kun Zhang. 2022. Latent hierarchical causal structure discovery with rank constraints. Advances in neural information processing systems 35 (2022), 5549-5561."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3703155"},{"key":"e_1_3_2_1_23_1","first-page":"18087","article-title":"Learning latent causal graphs via mixture oracles","volume":"34","author":"Kivva Bohdan","year":"2021","unstructured":"Bohdan Kivva, Goutham Rajendran, Pradeep Ravikumar, and Bryon Aragam. 2021. Learning latent causal graphs via mixture oracles. NeurIPS 34 (2021), 18087-18101.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_24_1","first-page":"1655","article-title":"Causal clustering for 1-factor measurement models","author":"Kummerfeld Erich","year":"2016","unstructured":"Erich Kummerfeld and Joseph Ramsey. 2016. Causal clustering for 1-factor measurement models. In KDD. 1655-1664.","journal-title":"KDD."},{"key":"e_1_3_2_1_25_1","volume-title":"Multi-agent causal discovery using large language models. arXiv preprint arXiv:2407.15073","author":"Le Hao Duong","year":"2024","unstructured":"Hao Duong Le, Xin Xia, and Zhang Chen. 2024. Multi-agent causal discovery using large language models. arXiv preprint arXiv:2407.15073 (2024)."},{"key":"e_1_3_2_1_26_1","unstructured":"Ao Li Yuexiang Xie Songze Li Fugee Tsung Bolin Ding and Yaliang Li. 2025. Agent-Oriented Planning in Multi-Agent Systems. In ICLR."},{"key":"e_1_3_2_1_27_1","first-page":"51991","article-title":"Camel: Communicative agents for'' mind'' exploration of large language model society","volume":"36","author":"Li Guohao","year":"2023","unstructured":"Guohao Li, Hasan Hammoud, Hani Itani, Dmitrii Khizbullin, and Bernard Ghanem. 2023. Camel: Communicative agents for'' mind'' exploration of large language model society. NeurIPS 36 (2023), 51991-52008.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_28_1","volume-title":"Transactions on Machine Learning Research","author":"Li Junyou","year":"2024","unstructured":"Junyou Li, Qin Zhang, Yangbin Yu, Qiang Fu, and Deheng Ye. 2024. More Agents Is All You Need. Transactions on Machine Learning Research (2024)."},{"key":"e_1_3_2_1_29_1","first-page":"17889","article-title":"Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate","author":"Liang Tian","year":"2024","unstructured":"Tian Liang, Zhiwei He, Wenxiang Jiao, Xing Wang, Yan Wang, Rui Wang, Yujiu Yang, Shuming Shi, and Zhaopeng Tu. 2024. Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate. In EMNLP. 17889-17904.","journal-title":"EMNLP."},{"key":"e_1_3_2_1_30_1","volume-title":"arXiv:2508.02076","author":"Liang Yunhao","year":"2025","unstructured":"Yunhao Liang, Yuan Qu, Jingyuan Yang, Shaochong Lin, and Zuo-Jun Max Shen. 2025. Everyone Contributes! Incentivizing Strategic Cooperation in Multi-LLM Systems via Sequential Public Goods Games. arXiv:2508.02076 (2025)."},{"key":"e_1_3_2_1_31_1","volume-title":"Groupdebate: Enhancing the efficiency of multi-agent debate using group discussion. arXiv:2409.14051","author":"Liu Tongxuan","year":"2024","unstructured":"Tongxuan Liu, Xingyu Wang, Weizhe Huang, Wenjiang Xu, Yuting Zeng, Lei Jiang, Hailong Yang, and Jing Li. 2024. Groupdebate: Enhancing the efficiency of multi-agent debate using group discussion. arXiv:2409.14051 (2024)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i13.29328"},{"key":"e_1_3_2_1_33_1","volume-title":"SkipNode: On alleviating performance degradation for deep graph convolutional networks. TKDE","author":"Lu Weigang","year":"2024","unstructured":"Weigang Lu, Yibing Zhan, Binbin Lin, Ziyu Guan, Liu Liu, Baosheng Yu, Wei Zhao, Yaming Yang, and Dacheng Tao. 2024. SkipNode: On alleviating performance degradation for deep graph convolutional networks. TKDE (2024), 7030-7043."},{"key":"e_1_3_2_1_34_1","first-page":"1","article-title":"Recursive causal discovery","volume":"26","author":"Mokhtarian Ehsan","year":"2025","unstructured":"Ehsan Mokhtarian, Sepehr Elahi, Sina Akbari, and Negar Kiyavash. 2025. Recursive causal discovery. JMLR 26, 61 (2025), 1-65.","journal-title":"JMLR"},{"key":"e_1_3_2_1_35_1","volume-title":"Forty-first International Conference on Machine Learning.","author":"Ng Ignavier","year":"2024","unstructured":"Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, and Kun Zhang. 2024. Score-based causal discovery of latent variable causal models. In Forty-first International Conference on Machine Learning."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511803161"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3241036"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2670315"},{"key":"e_1_3_2_1_39_1","unstructured":"Yujia Qin Shihao Liang Yining Ye Kunlun Zhu Lan Yan Yaxi Lu Yankai Lin Xin Cong Xiangru Tang Bill Qian et al. 2024. ToolLLM: Facilitating Large Language Models to Master 16000 Real-world APIs. In ICLR."},{"key":"e_1_3_2_1_40_1","first-page":"4295","article-title":"QMIX","author":"Rashid Tabish","year":"2018","unstructured":"Tabish Rashid, Mikayel Samvelyan, Christian Schroeder, Gregory Farquhar, Jakob Foerster, and Shimon Whiteson. 2018. QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. In ICML. 4295-4304.","journal-title":"In ICML."},{"key":"e_1_3_2_1_41_1","volume-title":"Towards scientific intelligence: A survey of llm-based scientific agents. arXiv preprint arXiv:2503.24047","author":"Ren Shuo","year":"2025","unstructured":"Shuo Ren, Pu Jian, Zhenjiang Ren, Chunlin Leng, Can Xie, and Jiajun Zhang. 2025. Towards scientific intelligence: A survey of llm-based scientific agents. arXiv preprint arXiv:2503.24047 (2025)."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","first-page":"15841","DOI":"10.52202\/079017-0506","article-title":"Observational scaling laws and the predictability of langauge model performance","volume":"37","author":"Ruan Yangjun","year":"2024","unstructured":"Yangjun Ruan, Chris J Maddison, and Tatsunori B Hashimoto. 2024. Observational scaling laws and the predictability of langauge model performance. Advances in Neural Information Processing Systems 37 (2024), 15841-15892.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_43_1","first-page":"1","article-title":"Learning linear non-Gaussian causal models in the presence of latent variables","volume":"21","author":"Salehkaleybar Saber","year":"2020","unstructured":"Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, and Kun Zhang. 2020. Learning linear non-Gaussian causal models in the presence of latent variables. Journal of Machine Learning Research 21, 39 (2020), 1-24.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_44_1","article-title":"A linear non-Gaussian acyclic model for causal discovery","volume":"7","author":"Shimizu Shohei","year":"2006","unstructured":"Shohei Shimizu, Patrik O Hoyer, Aapo Hyv\u00e4rinen, Antti Kerminen, and Michael Jordan. 2006. A linear non-Gaussian acyclic model for causal discovery. Journal of Machine Learning Research 7, 10 (2006).","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_45_1","volume-title":"prediction, and search","author":"Spirtes Peter","unstructured":"Peter Spirtes, Clark N Glymour, and Richard Scheines. 2000. Causation, prediction, and search. MIT press."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-024-40231-1"},{"key":"e_1_3_2_1_47_1","unstructured":"Ryan Wong Jiawei Wang Junjie Zhao Li Chen Yan Gao Long Zhang Xuan Zhou Zuo Wang Kai Xiang Ge Zhang et al. 2025. WideSearch: Benchmarking Agentic Broad Info-Seeking. arXiv preprint arXiv:2508.07999 (2025)."},{"key":"e_1_3_2_1_48_1","volume-title":"Autogen: Enabling next-gen LLM applications via multi-agent conversations. In COLM.","author":"Wu Qingyun","year":"2024","unstructured":"Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Jiale Liu, et al. 2024. Autogen: Enabling next-gen LLM applications via multi-agent conversations. In COLM."},{"key":"e_1_3_2_1_49_1","first-page":"14891","article-title":"Generalized independent noise condition for estimating latent variable causal graphs","volume":"33","author":"Xie Feng","year":"2020","unstructured":"Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, and Kun Zhang. 2020. Generalized independent noise condition for estimating latent variable causal graphs. NeurIPS 33 (2020), 14891-14902.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_50_1","first-page":"41618","article-title":"Self-evaluation guided beam search for reasoning","volume":"36","author":"Xie Yuxi","year":"2023","unstructured":"Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, James Xu Zhao, Min-Yen Kan, Junxian He, and Michael Xie. 2023. Self-evaluation guided beam search for reasoning. NeurIPS 36 (2023), 41618-41650.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_51_1","unstructured":"Xie Yi Zhanke Zhou Chentao Cao Qiyu Niu Tongliang Liu and Bo Han. 2025. From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium. In ICML."},{"key":"e_1_3_2_1_52_1","unstructured":"Guibin Zhang Muxin Fu Guancheng Wan Miao Yu Kun Wang and Shuicheng Yan. 2025. G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems. In NeurIPS."},{"key":"e_1_3_2_1_53_1","volume-title":"Sirius: Selfimproving multi-agent systems via bootstrapped reasoning. arXiv:2502.04780","author":"Zhao Wanjia","year":"2025","unstructured":"Wanjia Zhao, Mert Yuksekgonul, Shirley Wu, and James Zou. 2025. Sirius: Selfimproving multi-agent systems via bootstrapped reasoning. arXiv:2502.04780 (2025)."},{"key":"e_1_3_2_1_54_1","first-page":"4107","article-title":"MULAN: multi-modal causal structure learning and root cause analysis for microservice systems","author":"Zheng Lecheng","year":"2024","unstructured":"Lecheng Zheng, Zhengzhang Chen, Jingrui He, and Haifeng Chen. 2024. MULAN: multi-modal causal structure learning and root cause analysis for microservice systems. In WWW. 4107-4116.","journal-title":"WWW."},{"key":"e_1_3_2_1_55_1","first-page":"6677","article-title":"Causal inference with latent variables: Recent advances and future prospectives","author":"Zhu Yaochen","year":"2024","unstructured":"Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, and Jundong Li. 2024. Causal inference with latent variables: Recent advances and future prospectives. In KDD. 6677-6687.","journal-title":"KDD."}],"event":{"name":"WWW '26: The ACM Web Conference 2026","location":"Dubai United Arab Emirates","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2026"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3774904.3792244","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T07:51:51Z","timestamp":1783151511000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3774904.3792244"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,12]]},"references-count":55,"alternative-id":["10.1145\/3774904.3792244","10.1145\/3774904"],"URL":"https:\/\/doi.org\/10.1145\/3774904.3792244","relation":{},"subject":[],"published":{"date-parts":[[2026,4,12]]},"assertion":[{"value":"2026-04-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}