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Inf. Syst."],"published-print":{"date-parts":[[2026,3,31]]},"abstract":"<jats:p>Despite increasing research attention to text ranking, most studies focus on monolingual scenarios, with a particular emphasis on English-language contexts. This narrow focus limits the applicability of ranking models in cross-lingual contexts, such as ranking Chinese documents based on English queries. Recent advances in large language models (LLMs) have significantly reduced inter-language barriers through pre-training on extensive multilingual corpora, thus facilitating the study of multilingual text ranking (MTR). In this work, we explore the potential of LLMs in MTR tasks. Specifically, we first introduce an MTR benchmark encompassing both monolingual and cross-lingual scenarios. Then, we propose a two-stage training pipeline to alleviate the misalignment between LLMs and text ranking. Lastly, we adapt this training pipeline to multilingual scenarios from the perspective of training data and methods. Our experiments on the MTR benchmark demonstrate that the proposed multilingual two-stage training pipeline significantly improves LLM ranking performance in both monolingual and cross-lingual scenarios, particularly in out-domain settings. We complement these findings with a thorough analysis to deepen the understanding of our approach.<\/jats:p>","DOI":"10.1145\/3788859","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T10:05:52Z","timestamp":1768817152000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Progressive Adaptation of Large Language Models for Multilingual Text Ranking"],"prefix":"10.1145","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7932-6684","authenticated-orcid":false,"given":"Longhui","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Computing and Intelligence, Harbin Institute of Technology (Shenzhen), Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6581-7783","authenticated-orcid":false,"given":"Yanzhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Coalition of Independent Scholars, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6570-9406","authenticated-orcid":false,"given":"Dingkun","family":"Long","sequence":"additional","affiliation":[{"name":"National Coalition of Independent Scholars, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8412-359X","authenticated-orcid":false,"given":"Pengjun","family":"Xie","sequence":"additional","affiliation":[{"name":"National Coalition of Independent Scholars, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6335-1340","authenticated-orcid":false,"given":"Meishan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Computing and Intelligence, Harbin Institute of Technology (Shenzhen), Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3262-3734","authenticated-orcid":false,"given":"Jing","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Computing and Intelligence, Harbin Institute of Technology (Shenzhen), Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3895-5510","authenticated-orcid":false,"given":"Min","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Computing and Intelligence, Harbin Institute of Technology (Shenzhen), Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,3,2]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"1","volume-title":"Proceedings of the 6th Conference on Machine Translation","author":"Akhbardeh Farhad","year":"2021","unstructured":"Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, Ond\u0159ej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. 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