{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T03:25:05Z","timestamp":1781234705768,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","funder":[{"name":"National Natural Science Foundation of China","award":["62372431, 62472408 and 62441229"],"award-info":[{"award-number":["62372431, 62472408 and 62441229"]}]},{"name":"Strategic Priority Research Program of the CAS","award":["XDB0680301"],"award-info":[{"award-number":["XDB0680301"]}]},{"name":"National Key Research and Development Program of China","award":["2023YFA1011602"],"award-info":[{"award-number":["2023YFA1011602"]}]},{"name":"Lenovo- CAS Joint Lab Youth Scientist Project","award":["JCKY2022130C039"],"award-info":[{"award-number":["JCKY2022130C039"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,12,7]]},"DOI":"10.1145\/3767695.3769505","type":"proceedings-article","created":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T17:14:58Z","timestamp":1764782098000},"page":"47-54","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["VeriCite: Towards Reliable Citations in Retrieval-Augmented Generation via Rigorous Verification"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-4285-2137","authenticated-orcid":false,"given":"Haosheng","family":"Qian","sequence":"first","affiliation":[{"name":"State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4317-2702","authenticated-orcid":false,"given":"Yixing","family":"Fan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9509-8674","authenticated-orcid":false,"given":"Jiafeng","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4294-2541","authenticated-orcid":false,"given":"Ruqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1690-8430","authenticated-orcid":false,"given":"Qi","family":"Chen","sequence":"additional","affiliation":[{"name":"Meituan, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0684-6205","authenticated-orcid":false,"given":"Dawei","family":"Yin","sequence":"additional","affiliation":[{"name":"Baidu Inc, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6978-5406","authenticated-orcid":false,"given":"Xueqi","family":"Cheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,12,6]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et al. 2020. Language models are few-shot learners. Advances in neural information processing systems Vol. 33 (2020) 1877-1901."},{"key":"e_1_3_2_1_2_1","volume-title":"Computational Linguistics","volume":"41","author":"Dagan Ido","year":"2015","unstructured":"Ido Dagan, Dan Roth, Mark Sammons, and Fabio Massimo Zanzotto. 2015. Recognizing Textual Entailment: Models and Applications. Computational Linguistics, Vol. 41, 1 (2015)."},{"key":"e_1_3_2_1_3_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_4_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1346"},{"key":"e_1_3_2_1_5_1","volume-title":"TrustRAG: An Information Assistant with Retrieval Augmented Generation. arXiv preprint arXiv:2502.13719","author":"Fan Yixing","year":"2025","unstructured":"Yixing Fan, Qiang Yan, Wenshan Wang, Jiafeng Guo, Ruqing Zhang, and Xueqi Cheng. 2025. TrustRAG: An Information Assistant with Retrieval Augmented Generation. arXiv preprint arXiv:2502.13719 (2025)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.76"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.910"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.398"},{"key":"e_1_3_2_1_9_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, Yi Dai, Jiawei Sun, and Haofen Wang. 2023b. Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv:2312.10997 (2023)."},{"key":"e_1_3_2_1_10_1","volume-title":"Chatglm: A family of large language models from glm-130b to glm-4 all tools. arXiv preprint arXiv:2406.12793","author":"Aohan Zeng Team GLM","year":"2024","unstructured":"Team GLM, Aohan Zeng, Bin Xu, Bowen Wang, Chenhui Zhang, Da Yin, Dan Zhang, Diego Rojas, Guanyu Feng, Hanlin Zhao, et al., 2024. Chatglm: A family of large language models from glm-130b to glm-4 all tools. arXiv preprint arXiv:2406.12793 (2024)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331403"},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 3905-3920","author":"Honovich Or","year":"2022","unstructured":"Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, and Yossi Matias. 2022. TRUE: Re-evaluating Factual Consistency Evaluation. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 3905-3920."},{"key":"e_1_3_2_1_13_1","volume-title":"Benchmarking large language models in complex question answering attribution using knowledge graphs. arXiv preprint arXiv:2401.14640","author":"Hu Nan","year":"2024","unstructured":"Nan Hu, Jiaoyan Chen, Yike Wu, Guilin Qi, Sheng Bi, Tongtong Wu, and Jeff Z Pan. 2024. Benchmarking large language models in complex question answering attribution using knowledge graphs. arXiv preprint arXiv:2401.14640 (2024)."},{"key":"e_1_3_2_1_14_1","volume-title":"Citation: A key to building responsible and accountable large language models. arXiv preprint arXiv:2307.02185","author":"Huang Jie","year":"2023","unstructured":"Jie Huang and Kevin Chen-Chuan Chang. 2023. Citation: A key to building responsible and accountable large language models. arXiv preprint arXiv:2307.02185 (2023)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3571730"},{"key":"e_1_3_2_1_16_1","first-page":"9459","article-title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","volume":"33","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, et al., 2020. Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in Neural Information Processing Systems, Vol. 33 (2020), 9459-9474.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_17_1","volume-title":"Improving Attributed Text Generation of Large Language Models via Preference Learning. arXiv preprint arXiv:2403.18381","author":"Li Dongfang","year":"2024","unstructured":"Dongfang Li, Zetian Sun, Baotian Hu, Zhenyu Liu, Xinshuo Hu, Xuebo Liu, and Min Zhang. 2024. Improving Attributed Text Generation of Large Language Models via Preference Learning. arXiv preprint arXiv:2403.18381 (2024)."},{"key":"e_1_3_2_1_18_1","volume-title":"Rouge: A package for automatic evaluation of summaries. In Text summarization branches out. 74-81.","author":"Lin Chin-Yew","year":"2004","unstructured":"Chin-Yew Lin. 2004. Rouge: A package for automatic evaluation of summaries. In Text summarization branches out. 74-81."},{"key":"e_1_3_2_1_19_1","unstructured":"Aixin Liu Bei Feng Bing Xue Bingxuan Wang Bochao Wu Chengda Lu Chenggang Zhao Chengqi Deng Chenyu Zhang Chong Ruan et al. 2024a. Deepseek-v3 technical report. arXiv preprint arXiv:2412.19437 (2024)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599931"},{"key":"e_1_3_2_1_21_1","volume-title":"Invar-RAG: Invariant LLM-aligned Retrieval for Better Generation. arXiv preprint arXiv:2411.07021","author":"Liu Ziwei","year":"2024","unstructured":"Ziwei Liu, Liang Zhang, Qian Li, Jianghua Wu, and Guangxu Zhu. 2024b. Invar-RAG: Invariant LLM-aligned Retrieval for Better Generation. arXiv preprint arXiv:2411.07021 (2024)."},{"key":"e_1_3_2_1_22_1","volume-title":"AmbigQA: Answering ambiguous open-domain questions. arXiv preprint arXiv:2004.10645","author":"Min Sewon","year":"2020","unstructured":"Sewon Min, Julian Michael, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2020. AmbigQA: Answering ambiguous open-domain questions. arXiv preprint arXiv:2004.10645 (2020)."},{"key":"e_1_3_2_1_23_1","volume-title":"Webgpt: Browser-assisted question-answering with human feedback. arXiv preprint arXiv:2112.09332","author":"Nakano Reiichiro","year":"2021","unstructured":"Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al., 2021. Webgpt: Browser-assisted question-answering with human feedback. arXiv preprint arXiv:2112.09332 (2021)."},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 311-318","author":"Papineni Kishore","year":"2002","unstructured":"Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 311-318."},{"key":"e_1_3_2_1_25_1","volume-title":"The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track.","author":"Press Ori","year":"2024","unstructured":"Ori Press, Andreas Hochlehnert, Ameya Prabhu, Vishaal Udandarao, Ofir Press, and Matthias Bethge. 2024. CiteME: Can Language Models Accurately Cite Scientific Claims?. In The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-naacl.97"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1162\/coli_a_00486"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.249"},{"key":"e_1_3_2_1_29_1","volume-title":"Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347","author":"Schulman John","year":"2017","unstructured":"John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017. Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347 (2017)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.320"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.566"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.469"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.923"},{"key":"e_1_3_2_1_34_1","volume-title":"Cassidy Hardin, Surya Bhupatiraju, L\u00e9onard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ram\u00e9, et al.","author":"Team Gemma","year":"2024","unstructured":"Gemma Team, Morgane Riviere, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, L\u00e9onard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ram\u00e9, et al., 2024. Gemma 2: Improving open language models at a practical size. arXiv preprint arXiv:2408.00118 (2024)."},{"key":"e_1_3_2_1_35_1","unstructured":"Nandan Thakur Luiz Bonifacio Xinyu Zhang Odunayo Ogundepo Ehsan Kamalloo David Alfonso-Hermelo Xiaoguang Li Qun Liu Boxing Chen Mehdi Rezagholizadeh et al. 2023. NoMIRACL: Knowing When You Don't Know for Robust Multilingual Retrieval-Augmented Generation. arXiv preprint arXiv:2312.11361 (2023)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00475"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.557"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/2766462.2767710"},{"key":"e_1_3_2_1_39_1","unstructured":"An Yang Baosong Yang Beichen Zhang Binyuan Hui Bo Zheng Bowen Yu Chengyuan Li Dayiheng Liu Fei Huang Haoran Wei et al. 2024. Qwen2. 5 technical report. arXiv preprint arXiv:2412.15115 (2024)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1259"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.435"},{"key":"e_1_3_2_1_42_1","volume-title":"LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QA. arXiv preprint arXiv:2409.02897","author":"Zhang Jiajie","year":"2024","unstructured":"Jiajie Zhang, Yushi Bai, Xin Lv, Wanjun Gu, Danqing Liu, Minhao Zou, Shulin Cao, Lei Hou, Yuxiao Dong, Ling Feng, and Juanzi Li. 2024. LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QA. arXiv preprint arXiv:2409.02897 (2024)."}],"event":{"name":"SIGIR-AP 2025:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","location":"Xi'an China","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region"],"original-title":[],"deposited":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T17:20:44Z","timestamp":1764782444000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3767695.3769505"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,6]]},"references-count":42,"alternative-id":["10.1145\/3767695.3769505","10.1145\/3767695"],"URL":"https:\/\/doi.org\/10.1145\/3767695.3769505","relation":{},"subject":[],"published":{"date-parts":[[2025,12,6]]},"assertion":[{"value":"2025-12-06","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}