{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T04:13:04Z","timestamp":1749701584653,"version":"3.41.0"},"reference-count":39,"publisher":"MIT Press","license":[{"start":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T00:00:00Z","timestamp":1749600000000},"content-version":"vor","delay-in-days":161,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Recent approaches to multilingual open- domain question answering (MLODQA) have achieved promising results given abundant language-specific training data. However, the considerable annotation cost limits the application of these methods for underrepresented languages. We introduce a few-shot learning approach to synthesize large-scale multilingual data from large language models (LLMs). Our method begins with large-scale self-supervised pre-training using WikiData, followed by training on high-quality synthetic multilingual data generated by prompting LLMs with few-shot supervision. The final model, FsModQA, significantly outperforms existing few-shot and supervised baselines in MLODQA and cross-lingual and monolingual retrieval. We further show our method can be extended for effective zero-shot adaptation to new languages through a cross-lingual prompting strategy with only English-supervised data, making it a general and applicable solution for MLODQA tasks without costly large-scale annotation.<\/jats:p>","DOI":"10.1162\/tacl_a_00750","type":"journal-article","created":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T16:25:57Z","timestamp":1749659157000},"page":"481-504","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":0,"title":["Few-Shot Multilingual Open-Domain QA from Five Examples"],"prefix":"10.1162","volume":"13","author":[{"given":"Fan","family":"Jiang","sequence":"first","affiliation":[{"name":"School of Computing and Information Systems, The University of Melbourne, Victoria, Australia. 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