{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T17:00:54Z","timestamp":1792170054012,"version":"4.4.0"},"publisher-location":"New York, NY, USA","reference-count":65,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589334.3645701","type":"proceedings-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T07:08:13Z","timestamp":1715152093000},"page":"1529-1538","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Query in Your Tongue: Reinforce Large Language Models with Retrievers for Cross-lingual Search Generative Experience"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2628-8044","authenticated-orcid":false,"given":"Ping","family":"Guo","sequence":"first","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences &amp; School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4520-4520","authenticated-orcid":false,"given":"Yue","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences &amp; School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3848-7040","authenticated-orcid":false,"given":"Yanan","family":"Cao","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, School of Cyber Security, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2835-3150","authenticated-orcid":false,"given":"Yubing","family":"Ren","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, School of Cyber Security, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4089-4390","authenticated-orcid":false,"given":"Yunpeng","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences &amp; University of Chinese Academy of Sciences, School of Cyber Security, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0320-7520","authenticated-orcid":false,"given":"Heyan","family":"Huang","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.eacl-demo.1"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.46"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.mia-1.11"},{"key":"e_1_3_2_2_4_1","unstructured":"Arian Askari Mohammad Aliannejadi Evangelos Kanoulas and Suzan Verberne. 2023. Generating Synthetic Documents for Cross-Encoder Re-Rankers: A Comparative Study of ChatGPT and Human Experts. arXiv:2305.02320 [cs.IR]"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341981.3344236"},{"key":"e_1_3_2_2_6_1","volume-title":"CLEF 2002 - Overview of Results. In Advances in Cross- Language Information Retrieval, Carol Peters, Martin Braschler, Julio Gonzalo, and Michael Kluck (Eds.). Springer Berlin Heidelberg","author":"Braschler Martin","year":"2003","unstructured":"Martin Braschler. 2003. CLEF 2002 - Overview of Results. In Advances in Cross- Language Information Retrieval, Carol Peters, Martin Braschler, Julio Gonzalo, and Michael Kluck (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 9--27."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557271"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463027"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.62"},{"key":"e_1_3_2_2_10_1","unstructured":"Jiazhan Feng Chongyang Tao Xiubo Geng Tao Shen Can Xu Guodong Long Dongyan Zhao and Daxin Jiang. 2023. Knowledge Refinement via Interaction Between Search Engines and Large Language Models. arXiv:2305.07402 [cs.CL]"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.90"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583383"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.438"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.581"},{"key":"e_1_3_2_2_15_1","volume-title":"Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1024--1035","author":"Huang Kung-Hsiang","year":"2022","unstructured":"Kung-Hsiang Huang, ChengXiang Zhai, and Heng Ji. 2022. CONCRETE: Improving Cross-lingual Fact-checking with Cross-lingual Retrieval. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1024--1035. https:\/\/aclanthology.org\/2022.coling-1.86"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482452"},{"key":"e_1_3_2_2_17_1","unstructured":"Zhiqi Huang Puxuan Yu and James Allan. 2023. Cross-lingual Knowledge Transfer via Distillation for Multilingual Information Retrieval. arXiv:2302.13400 cs.IR"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570468"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591769"},{"key":"e_1_3_2_2_20_1","volume-title":"Unsupervised Dense Information Retrieval with Contrastive Learning. Transactions on Machine Learning Research","author":"Izacard Gautier","year":"2022","unstructured":"Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022. Unsupervised Dense Information Retrieval with Contrastive Learning. Transactions on Machine Learning Research (2022). https:\/\/openreview.net\/forum?id=jKN1pXi7b0"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"crossref","unstructured":"Vitor Jeronymo Roberto Lotufo and Rodrigo Nogueira. 2023. NeuralMind-UNICAMP at 2022 TREC NeuCLIR: Large Boring Rerankers for Cross-lingual Retrieval. arXiv:2303.16145 [cs.IR]","DOI":"10.6028\/NIST.SP.500-338.neuclir-NM.unicamp"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00407"},{"key":"e_1_3_2_2_23_1","volume-title":"Proceedings of the workshop on Cross-Language Search and Summarization of Text and Speech (CLSSTS2020)","author":"Jiang Zhuolin","year":"2020","unstructured":"Zhuolin Jiang, Amro El-Jaroudi, William Hartmann, Damianos Karakos, and Lingjun Zhao. 2020. Cross-lingual Information Retrieval with BERT. In Proceedings of the workshop on Cross-Language Search and Summarization of Text and Speech (CLSSTS2020). European Language Resources Association, Marseille, France, 26--31. https:\/\/aclanthology.org\/2020.clssts-1.5"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463048"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.naacl-main.329"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Jimmy Lin David Alfonso-Hermelo Vitor Jeronymo Ehsan Kamalloo Carlos Lassance Rodrigo Nogueira Odunayo Ogundepo Mehdi Rezagholizadeh Nandan Thakur Jheng-Hong Yang and Xinyu Zhang. 2023. Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval. arXiv:2304.01019 [cs.IR]","DOI":"10.6028\/NIST.SP.500-338.neuclir-h2oloo"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.193"},{"key":"e_1_3_2_2_28_1","volume-title":"Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1071--1082","author":"Litschko Robert","year":"2022","unstructured":"Robert Litschko, Ivan Vulic, and Goran Glava?. 2022. Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1071--1082. https:\/\/aclanthology.org\/2022.coling-1.90"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/978--3-030--72113--8_23"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-022-09406-x"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.coling-main.323"},{"key":"e_1_3_2_2_32_1","volume-title":"MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering. https\/\/arxiv.org\/pdf\/2007.15207.pdf","author":"Longpre Shayne","year":"2020","unstructured":"Shayne Longpre, Yi Lu, and Joachim Daiber. 2020. MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering. https\/\/arxiv.org\/pdf\/2007.15207.pdf"},{"key":"e_1_3_2_2_33_1","unstructured":"Iain Mackie Shubham Chatterjee and Jeffrey Dalton. 2023. Generative and Pseudo-Relevant Feedback for Sparse Dense and Learned Sparse Retrieval. arXiv:2305.07477 cs.IR"},{"key":"e_1_3_2_2_34_1","volume-title":"GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval. arXiv:2306.09938 cs.IR","author":"Mackie Iain","year":"2023","unstructured":"Iain Mackie, Ivan Sekulic, Shubham Chatterjee, Jeffrey Dalton, and Fabio Crestani. 2023. GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval. arXiv:2306.09938 cs.IR"},{"key":"e_1_3_2_2_35_1","unstructured":"Kelong Mao Zhicheng Dou Haonan Chen Fengran Mo and Hongjin Qian. 2023. Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search. arXiv:2303.06573 cs.IR"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"crossref","unstructured":"Niklas Muennighoff Thomas Wang Lintang Sutawika Adam Roberts Stella Biderman Teven Le Scao M Saiful Bari Sheng Shen Zheng-Xin Yong Hailey Schoelkopf Xiangru Tang Dragomir Radev Alham Fikri Aji Khalid Almubarak Samuel Albanie Zaid Alyafeai Albert Webson Edward Raff and Colin Raffel. 2023. Crosslingual Generalization through Multitask Finetuning. arXiv:2211.01786 cs.CL","DOI":"10.18653\/v1\/2023.acl-long.891"},{"key":"e_1_3_2_2_37_1","unstructured":"Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright Pamela Mishkin Chong Zhang Sandhini Agarwal Katarina Slama Alex Ray John Schulman Jacob Hilton Fraser Kelton Luke Miller Maddie Simens Amanda Askell PeterWelinder Paul Christiano Jan Leike and Ryan Lowe. 2022. Training language models to follow instructions with human feedback. arXiv:2203.02155 cs.CL"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"crossref","unstructured":"Zhen Qin Rolf Jagerman Kai Hui Honglei Zhuang Junru Wu Jiaming Shen Tianqi Liu Jialu Liu Donald Metzler Xuanhui Wang and Michael Bendersky. 2023. Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. arXiv:2306.17563 [cs.IR]","DOI":"10.18653\/v1\/2024.findings-naacl.97"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.203"},{"key":"e_1_3_2_2_40_1","unstructured":"John Schulman Filip Wolski Prafulla Dhariwal Alec Radford and Oleg Klimov. 2017. Proximal Policy Optimization Algorithms. arXiv:1707.06347 cs.LG"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Tao Shen Guodong Long Xiubo Geng Chongyang Tao Tianyi Zhou and Daxin Jiang. 2023. Large Language Models are Strong Zero-Shot Retriever. arXiv:2304.14233 cs.CL","DOI":"10.18653\/v1\/2024.findings-acl.943"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.mrl-1.24"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.naacl-main.30"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-industry.50"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.eacl-main.108"},{"key":"e_1_3_2_2_46_1","volume-title":"Oh (Eds.)","volume":"35","author":"Tay Yi","year":"2022","unstructured":"Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, Tal Schuster, William W Cohen, and Donald Metzler. 2022. Transformer Memory as a Differentiable Search Index. In Advances in Neural Information Processing Systems, S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 21831--21843. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2022\/file\/892840a6123b5ec99ebaab8be1530fba-Paper-Conference.pdf"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.557"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.mia-1.10"},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"crossref","unstructured":"Liang Wang Nan Yang and Furu Wei. 2023. Query2doc: Query Expansion with Large Language Models. arXiv:2303.07678 [cs.IR]","DOI":"10.18653\/v1\/2023.emnlp-main.585"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482050"},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.673"},{"key":"e_1_3_2_2_52_1","unstructured":"Linlong Xu Baosong Yang Xiaoyu Lv Tianchi Bi Dayiheng Liu and Haibo Zhang. 2021. Leveraging Advantages of Interactive and Non-Interactive Models for Vector-Based Cross-Lingual Information Retrieval. arXiv:2111.01992 [cs.CL]"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.470"},{"key":"e_1_3_2_2_54_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.502"},{"key":"e_1_3_2_2_55_1","unstructured":"Liang Yao Baosong Yang Haibo Zhang Weihua Luo and Boxing Chen. 2020. Exploiting Neural Query Translation into Cross Lingual Information Retrieval. arXiv:2010.13659 [cs.CL]"},{"key":"e_1_3_2_2_56_1","unstructured":"Zhewei Yao Reza Yazdani Aminabadi Olatunji Ruwase Samyam Rajbhandari Xiaoxia Wu Ammar Ahmad Awan Jeff Rasley Minjia Zhang Conglong Li Connor Holmes Zhongzhu Zhou Michael Wyatt Molly Smith Lev Kurilenko Heyang Qin Masahiro Tanaka Shuai Che Shuaiwen Leon Song and Yuxiong He. 2023. DeepSpeed-Chat: Easy Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales. arXiv:2308.01320 [cs.LG]"},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401322"},{"key":"e_1_3_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlpindustry.8"},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20355"},{"key":"e_1_3_2_2_60_1","volume-title":"The Eleventh International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=-bVsNeR56KS","author":"Zhang Shunyu","year":"2023","unstructured":"Shunyu Zhang, Yaobo Liang, MING GONG, Daxin Jiang, and Nan Duan. 2023. Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval. In The Eleventh International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=-bVsNeR56KS"},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3613447"},{"key":"e_1_3_2_2_62_1","unstructured":"Shengyao Zhuang Houxing Ren Linjun Shou Jian Pei Ming Gong Guido Zuccon and Daxin Jiang. 2023. Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation. arXiv:2206.10128 [cs.IR]"},{"key":"e_1_3_2_2_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591952"},{"key":"e_1_3_2_2_64_1","unstructured":"Daniel M. Ziegler Nisan Stiennon Jeffrey Wu Tom B. Brown Alec Radford Dario Amodei Paul Christiano and Geoffrey Irving. 2020. Fine-Tuning Language Models from Human Preferences. arXiv:1909.08593 [cs.CL]"},{"key":"e_1_3_2_2_65_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.167"}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645701","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589334.3645701","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:27:30Z","timestamp":1755822450000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645701"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":65,"alternative-id":["10.1145\/3589334.3645701","10.1145\/3589334"],"URL":"https:\/\/doi.org\/10.1145\/3589334.3645701","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}