{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T18:10:26Z","timestamp":1784139026487,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62293553, 62477036, 62192781"],"award-info":[{"award-number":["62293553, 62477036, 62192781"]}]},{"name":"Fundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China","award":["JYB2025XDXM116"],"award-info":[{"award-number":["JYB2025XDXM116"]}]},{"name":"The EPSRC project OntoEm","award":["EP&#x5c;&#x2f;Y017706&#x5c;&#x2f;1"],"award-info":[{"award-number":["EP&#x5c;&#x2f;Y017706&#x5c;&#x2f;1"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,7,20]]},"DOI":"10.1145\/3805712.3809650","type":"proceedings-article","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T17:06:26Z","timestamp":1784135186000},"page":"2464-2474","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploring Knowledge Conflicts for Faithful LLM Reasoning: Benchmark and Method"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2879-2703","authenticated-orcid":false,"given":"Tianzhe","family":"Zhao","sequence":"first","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4643-6750","authenticated-orcid":false,"given":"Jiaoyan","family":"Chen","sequence":"additional","affiliation":[{"name":"The University of Manchester, Manchester, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1238-7983","authenticated-orcid":false,"given":"Shuxiu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hunan University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2407-8307","authenticated-orcid":false,"given":"Haiping","family":"Zhu","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5650-0600","authenticated-orcid":false,"given":"Qika","family":"Lin","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6004-0675","authenticated-orcid":false,"given":"Jun","family":"Liu","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,7,19]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Knowledge Graphs, and Hierarchical Non-negative Matrix Factorization. arXiv preprint arXiv:2502.20364","author":"Barron Ryan C","year":"2025","unstructured":"Ryan C Barron, Maksim E Eren, Olga M Serafimova, Cynthia Matuszek, and Boian S Alexandrov. 2025. Bridging Legal Knowledge and AI: Retrieval-Augmented Generation with Vector Stores, Knowledge Graphs, and Hierarchical Non-negative Matrix Factorization. arXiv preprint arXiv:2502.20364 (2025)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.146"},{"key":"e_1_3_2_1_3_1","volume-title":"Rag-based question answering over heterogeneous data and text. arXiv preprint arXiv:2412.07420","author":"Christmann Philipp","year":"2024","unstructured":"Philipp Christmann and Gerhard Weikum. 2024. Rag-based question answering over heterogeneous data and text. arXiv preprint arXiv:2412.07420 (2024)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3726302.3730071"},{"key":"e_1_3_2_1_5_1","unstructured":"Abhimanyu Dubey Abhinav Jauhri Abhinav Pandey Abhishek Kadian Ahmad Al-Dahle Aiesha Letman Akhil Mathur Alan Schelten Amy Yang Angela Fan et al. 2024. The llama 3 herd of models. arXiv preprint arXiv:2407.21783 (2024)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671470"},{"key":"e_1_3_2_1_7_1","volume-title":"Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv:2312.10997","author":"Gao Yunfan","year":"2023","unstructured":"Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yixin Dai, Jiawei Sun, Haofen Wang, and Haofen Wang. 2023. Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv:2312.10997, Vol. 2, 1 (2023)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.emnlp-main.840"},{"key":"e_1_3_2_1_9_1","unstructured":"Albert Q. Jiang Alexandre Sablayrolles Arthur Mensch Chris Bamford Devendra Singh Chaplot Diego de Las Casas Florian Bressand Gianna Lengyel Guillaume Lample Lucile Saulnier L\u00e9lio Renard Lavaud Marie-Anne Lachaux Pierre Stock Teven Le Scao Thibaut Lavril Thomas Wang Timoth\u00e9e Lacroix and William El Sayed. 2023. Mistral 7B. CoRR Vol. abs\/2310.06825 (2023)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.63317\/4fisde58hr4n"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.acl-long.43"},{"key":"e_1_3_2_1_12_1","unstructured":"Patrick Lewis Ethan Perez Aleksandra Piktus Fabio Petroni Vladimir Karpukhin Naman Goyal Heinrich K\u00fcttler Mike Lewis Wen-tau Yih Tim Rockt\u00e4schel et al. 2020. Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in neural information processing systems Vol. 33 (2020) 9459-9474."},{"key":"e_1_3_2_1_13_1","volume-title":"The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=cPgh4gWZlz","author":"Li Xingxuan","year":"2024","unstructured":"Xingxuan Li, Ruochen Zhao, Yew Ken Chia, Bosheng Ding, Shafiq Joty, Soujanya Poria, and Lidong Bing. 2024. Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources. In The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=cPgh4gWZlz"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.acl-long.230"},{"key":"e_1_3_2_1_15_1","unstructured":"Aixin Liu Aoxue Mei Bangcai Lin Bing Xue Bingxuan Wang Bingzheng Xu Bochao Wu Bowei Zhang Chaofan Lin Chen Dong et al. 2025a. DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models. arXiv preprint arXiv:2512.02556 (2025)."},{"key":"e_1_3_2_1_16_1","first-page":"3626","volume-title":"SKA-Bench: A Fine-Grained Benchmark for Evaluating Structured Knowledge Understanding of LLMs. In Findings of the Association for Computational Linguistics: EMNLP","author":"Liu Zhiqiang","year":"2025","unstructured":"Zhiqiang Liu, Enpei Niu, Yin Hua, Mengshu Sun, Lei Liang, Huajun Chen, and Wen Zhang. 2025b. SKA-Bench: A Fine-Grained Benchmark for Evaluating Structured Knowledge Understanding of LLMs. In Findings of the Association for Computational Linguistics: EMNLP 2025. Association for Computational Linguistics, Suzhou, China, 3626-3640."},{"key":"e_1_3_2_1_17_1","first-page":"1174","article-title":"Unifying Large Language Models and Knowledge Graphs for Question Answering: Recent Advances and Opportunities","author":"Ma Chuangtao","year":"2025","unstructured":"Chuangtao Ma, Yongrui Chen, Tianxing Wu, Arijit Khan, and Haofen Wang. 2025a. Unifying Large Language Models and Knowledge Graphs for Question Answering: Recent Advances and Opportunities.. In EDBT. 1174-1177.","journal-title":"EDBT."},{"key":"e_1_3_2_1_18_1","volume-title":"The Thirteenth International Conference on Learning Representations.","author":"Ma Shengjie","year":"2025","unstructured":"Shengjie Ma, Chengjin Xu, Xuhui Jiang, Muzhi Li, Huaren Qu, Cehao Yang, Jiaxin Mao, and Jian Guo. 2025b. Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation. In The Thirteenth International Conference on Learning Representations."},{"key":"e_1_3_2_1_19_1","first-page":"29430","volume-title":"International Conference on Representation Learning","volume":"2025","author":"Ming Yifei","year":"2025","unstructured":"Yifei Ming, Senthil Purushwalkam, Shrey Pandit, Zixuan Ke, Xuan-Phi Nguyen, Caiming Xiong, and Shafiq Joty. 2025. FaithEval: Can Your Language Model Stay Faithful to Context, Even If ''The Moon is Made of Marshmallows''. In International Conference on Representation Learning, Vol. 2025. 29430-29456."},{"key":"e_1_3_2_1_20_1","unstructured":"Mistral. 2025. Mistral-Large-3-675B-Instruct-2512. https:\/\/huggingface.co\/mistralai\/Mistral-Large-3-675B-Instruct-2512. Accessed: 2026-01-23."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3744746"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-88717-8_18"},{"key":"e_1_3_2_1_23_1","unstructured":"OpenAI. 2023. GPT-3.5 Turbo. https:\/\/platform.openai.com\/docs\/models\/gpt-3.5-turbo. Accessed: 2026-01-23."},{"key":"e_1_3_2_1_24_1","unstructured":"OpenAI. 2024. Hello GPT-4o. https:\/\/openai.com\/index\/hello-gpt-4o\/. Accessed: 2026-01-23."},{"key":"e_1_3_2_1_25_1","unstructured":"OpenAI. 2025a. GPT-5.1: A smarter more conversational ChatGPT. https:\/\/openai.com\/index\/gpt-5-1\/. Accessed: 2026-01-23."},{"key":"e_1_3_2_1_26_1","unstructured":"OpenAI. 2025b. OpenAI o3-mini. https:\/\/openai.com\/index\/openai-o3-mini\/. Accessed: 2026-01-23."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3777378","article-title":"Graph retrieval-augmented generation: A survey","volume":"44","author":"Peng Boci","year":"2025","unstructured":"Boci Peng, Yun Zhu, Yongchao Liu, Xiaohe Bo, Haizhou Shi, Chuntao Hong, Yan Zhang, and Siliang Tang. 2025. Graph retrieval-augmented generation: A survey. ACM Transactions on Information Systems, Vol. 44, 2 (2025), 1-52.","journal-title":"ACM Transactions on Information Systems"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/AIxSET62544.2024.00030"},{"key":"e_1_3_2_1_29_1","volume-title":"The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track.","author":"Su Zhaochen","year":"2024","unstructured":"Zhaochen Su, Jun Zhang, Xiaoye Qu, Tong Zhu, Yanshu Li, Jiashuo Sun, Juntao Li, Min Zhang, and Yu Cheng. 2024. $textbackslashtextttConflictBank$: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLMs. In The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1059"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.acl-long.1476"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.52202\/079017-4037"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.naacl-long.216"},{"key":"e_1_3_2_1_34_1","volume-title":"The Twelfth International Conference on Learning Representations.","author":"Xie Jian","year":"2023","unstructured":"Jian Xie, Kai Zhang, Jiangjie Chen, Renze Lou, and Yu Su. 2023. Adaptive chameleon or stubborn sloth: Revealing the behavior of large language models in knowledge conflicts. In The Twelfth International Conference on Learning Representations."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2025.3536008"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.486"},{"key":"e_1_3_2_1_37_1","unstructured":"An Yang Anfeng Li Baosong Yang Beichen Zhang Binyuan Hui Bo Zheng Bowen Yu Chang Gao Chengen Huang Chenxu Lv et al. 2025. Qwen3 technical report. arXiv preprint arXiv:2505.09388 (2025)."},{"key":"e_1_3_2_1_38_1","volume-title":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 201-206","author":"Richardson Matthew","year":"2016","unstructured":"Wen-tau Yih, Matthew Richardson, Christopher Meek, Ming-Wei Chang, and Jina Suh. 2016. 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). 201-206."},{"key":"e_1_3_2_1_39_1","volume-title":"Exploring Knowledge Poisoning Attacks to Retrieval-Augmented Generation. Information Fusion","author":"Zhao Tianzhe","year":"2025","unstructured":"Tianzhe Zhao, Jiaoyan Chen, Yanchi Ru, Haiping Zhu, Nan Hu, Jun Liu, and Qika Lin. 2025a. Exploring Knowledge Poisoning Attacks to Retrieval-Augmented Generation. Information Fusion (2025), 103900."},{"key":"e_1_3_2_1_40_1","unstructured":"Wayne Xin Zhao Kun Zhou Junyi Li Tianyi Tang Xiaolei Wang Yupeng Hou Yingqian Min Beichen Zhang Junjie Zhang Zican Dong et al. 2023. A survey of large language models. arXiv preprint arXiv:2303.18223 Vol. 1 2 (2023)."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3696410.3714782"},{"key":"e_1_3_2_1_42_1","first-page":"3827","volume-title":"34th USENIX Security Symposium (USENIX Security 25)","author":"Zou Wei","year":"2025","unstructured":"Wei Zou, Runpeng Geng, Binghui Wang, and Jinyuan Jia. 2025. : Knowledge corruption attacks to generation of large language models. In 34th USENIX Security Symposium (USENIX Security 25). 3827-3844."}],"event":{"name":"SIGIR '26: The 49th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Melbourne VIC Australia","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"deposited":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T17:27:28Z","timestamp":1784136448000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3805712.3809650"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,19]]},"references-count":42,"alternative-id":["10.1145\/3805712.3809650","10.1145\/3805712"],"URL":"https:\/\/doi.org\/10.1145\/3805712.3809650","relation":{},"subject":[],"published":{"date-parts":[[2026,7,19]]},"assertion":[{"value":"2026-07-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}