{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T05:15:22Z","timestamp":1784178922072,"version":"3.55.0"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030997359","type":"print"},{"value":"9783030997366","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-99736-6_26","type":"book-chapter","created":{"date-parts":[[2022,4,4]],"date-time":"2022-04-04T23:02:47Z","timestamp":1649113367000},"page":"382-396","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2283-7672","authenticated-orcid":false,"given":"Suraj","family":"Nair","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0051-1535","authenticated-orcid":false,"given":"Eugene","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7347-7086","authenticated-orcid":false,"given":"Dawn","family":"Lawrie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8107-4383","authenticated-orcid":false,"given":"Kevin","family":"Duh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0548-5751","authenticated-orcid":false,"given":"Paul","family":"McNamee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5628-1003","authenticated-orcid":false,"given":"Kenton","family":"Murray","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3866-3013","authenticated-orcid":false,"given":"James","family":"Mayfield","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1696-0407","authenticated-orcid":false,"given":"Douglas W.","family":"Oard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,4,5]]},"reference":[{"key":"26_CR1","doi-asserted-by":"crossref","unstructured":"Allan, J., et al.: INQUERY does battle with TREC-6. NIST Spec. Publ. 500\u2013240, 169\u2013206 (1998)","DOI":"10.6028\/NIST.SP.500-240.filtering-UMass"},{"key":"26_CR2","unstructured":"Bajaj, P., et al.: MS MARCO: a human generated machine reading comprehension dataset. arXiv preprint arXiv:1611.09268v3 (2018)"},{"key":"26_CR3","doi-asserted-by":"crossref","unstructured":"Bonab, H., Sarwar, S.M., Allan, J.: Training effective neural CLIR by bridging the translation gap. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 9\u201318. Association for Computing Machinery, New York, NY, USA, July 2020","DOI":"10.1145\/3397271.3401035"},{"key":"26_CR4","unstructured":"Bonifacio, L.H., Campiotti, I., Lotufo, R., Nogueira, R.: mMARCO: a multilingual version of MS MARCO passage ranking dataset. arXiv preprint arXiv:2108.13897 (2021)"},{"key":"26_CR5","doi-asserted-by":"crossref","unstructured":"Conneau, A., et al.: Unsupervised cross-lingual representation learning at scale. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 8440\u20138451. Association for Computational Linguistics, Online, July 2020","DOI":"10.18653\/v1\/2020.acl-main.747"},{"key":"26_CR6","doi-asserted-by":"crossref","unstructured":"Dai, Z., Xiong, C., Callan, J., Liu, Z.: Convolutional neural networks for soft-matching n-grams in ad-hoc search. In: Proceedings of the 11th ACM International Conference on Web Search and Data Mining, pp. 126\u2013134 (2018)","DOI":"10.1145\/3159652.3159659"},{"key":"26_CR7","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171\u20134186. Association for Computational Linguistics, Minneapolis, Minnesota, June 2019"},{"key":"26_CR8","unstructured":"Domhan, T., Denkowski, M., Vilar, D., Niu, X., Hieber, F., Heafield, K.: The sockeye 2 neural machine translation toolkit at AMTA 2020. In: Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), pp. 110\u2013115. Association for Machine Translation in the Americas, Virtual, October 2020"},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"Guo, J., Fan, Y., Ai, Q., Croft, W.B.: A deep relevance matching model for ad-hoc retrieval. In: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, pp. 55\u201364 (2016)","DOI":"10.1145\/2983323.2983769"},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Hui, K., Yates, A., Berberich, K., de Melo, G.: PACRR: a position-aware neural IR model for relevance matching. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 1049\u20131058. Association for Computational Linguistics, Copenhagen, Denmark, September 2017","DOI":"10.18653\/v1\/D17-1110"},{"key":"26_CR11","unstructured":"Jiang, Z., El-Jaroudi, A., Hartmann, W., Karakos, D., Zhao, L.: Cross-lingual information retrieval with BERT. arXiv preprint arXiv:2004.13005, April 2020"},{"key":"26_CR12","unstructured":"Johnson, J., Douze, M., J\u00e9gou, H.: Billion-scale similarity search with GPUs. arXiv preprint arXiv:1702.08734 (2017)"},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Khattab, O., Zaharia, M.: ColBERT: efficient and effective passage search via contextualized late interaction over BERT. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 39\u201348. Association for Computing Machinery, New York, NY, USA, July 2020","DOI":"10.1145\/3397271.3401075"},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Lawrie, D., Mayfield, J., Oard, D.W., Yang, E.: HC4: a new suite of test collections for ad hoc CLIR. In: Proceedings of the 44th European Conference on Information Retrieval (2021)","DOI":"10.1007\/978-3-030-99736-6_24"},{"issue":"4","key":"26_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-02181-7","volume":"14","author":"J Lin","year":"2021","unstructured":"Lin, J., Nogueira, R., Yates, A.: Pretrained transformers for text ranking: Bert and beyond. Synt. Lectur. Hum. Lang. Technol. 14(4), 1\u2013325 (2021)","journal-title":"Synt. Lectur. Hum. Lang. Technol."},{"key":"26_CR16","unstructured":"Liu, Y., et al.: Roberta: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)"},{"key":"26_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1007\/978-3-030-45442-5_31","volume-title":"Advances in Information Retrieval","author":"S MacAvaney","year":"2020","unstructured":"MacAvaney, S., Soldaini, L., Goharian, N.: Teaching a new dog old tricks: resurrecting multilingual retrieval using zero-shot learning. In: Jose, J.M., Yilmaz, E., Magalh\u00e3es, J., Castells, P., Ferro, N., Silva, M.J., Martins, F. (eds.) ECIR 2020. LNCS, vol. 12036, pp. 246\u2013254. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-45442-5_31"},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"MacAvaney, S., Yates, A., Cohan, A., Goharian, N.: Cedr: contextualized embeddings for document ranking. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1101\u20131104 (2019)","DOI":"10.1145\/3331184.3331317"},{"key":"26_CR19","doi-asserted-by":"crossref","unstructured":"McNamee, P., Mayfield, J.: Comparing cross-language query expansion techniques by degrading translation resources. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 159\u2013166 (2002)","DOI":"10.1145\/564376.564406"},{"key":"26_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"517","DOI":"10.1007\/978-3-540-31865-1_37","volume-title":"Advances in Information Retrieval","author":"I Ounis","year":"2005","unstructured":"Ounis, I., Amati, G., Plachouras, V., He, B., Macdonald, C., Johnson, D.: Terrier information retrieval platform. In: Losada, D.E., Fern\u00e1ndez-Luna, J.M. (eds.) ECIR 2005. LNCS, vol. 3408, pp. 517\u2013519. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/978-3-540-31865-1_37"},{"key":"26_CR21","doi-asserted-by":"crossref","unstructured":"Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 311\u2013318. Association for Computational Linguistics, Philadelphia, Pennsylvania, USA, July 2002","DOI":"10.3115\/1073083.1073135"},{"issue":"12","key":"26_CR22","doi-asserted-by":"publisher","first-page":"1067","DOI":"10.1002\/asi.1164","volume":"52","author":"C Peters","year":"2001","unstructured":"Peters, C., Braschler, M.: European research letter: cross-language system evaluation: the CLEF campaigns. J. Am. Soc. Inform. Sci. Technol. 52(12), 1067\u20131072 (2001)","journal-title":"J. Am. Soc. Inform. Sci. Technol."},{"key":"26_CR23","unstructured":"Peters, M.E., et al.: Deep contextualized word representations. In: Proceedings of NAACL-HLT, pp. 2227\u20132237 (2018)"},{"key":"26_CR24","doi-asserted-by":"crossref","unstructured":"Ponte, J.M., Croft, W.B.: A language modeling approach to information retrieval. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 275\u2013281 (1998)","DOI":"10.1145\/290941.291008"},{"key":"26_CR25","doi-asserted-by":"crossref","unstructured":"Post, M.: A call for clarity in reporting BLEU scores. In: Proceedings of the Third Conference on Machine Translation: Research Papers, pp. 186\u2013191. Association for Computational Linguistics, Brussels, Belgium, October 2018","DOI":"10.18653\/v1\/W18-6319"},{"key":"26_CR26","doi-asserted-by":"crossref","unstructured":"Robertson, S.E., Walker, S., Jones, S., et al.: Okapi at TREC-3. In: Overview of the Third Text REtrieval Conference (TREC-3) (1995)","DOI":"10.6028\/NIST.SP.500-225.city"},{"key":"26_CR27","doi-asserted-by":"crossref","unstructured":"Santhanam, K., Khattab, O., Saad-Falcon, J., Potts, C., Zaharia, M.: Colbertv2: effective and efficient retrieval via lightweight late interaction. arXiv preprint arXiv:2112.01488 (2021)","DOI":"10.18653\/v1\/2022.naacl-main.272"},{"key":"26_CR28","unstructured":"Shi, P., Lin, J.: Cross-lingual relevance transfer for document retrieval. arXiv preprint arXiv:1911.02989 (2019)"},{"key":"26_CR29","doi-asserted-by":"crossref","unstructured":"Shi, P., Zhang, R., Bai, H., Lin, J.: Cross-lingual training with dense retrieval for document retrieval. arXiv preprint arXiv:2109.01628 (2021)","DOI":"10.18653\/v1\/2021.mrl-1.24"},{"key":"26_CR30","unstructured":"Vaswani, A., et al.: Attention is all you need. arXiv preprint arXiv:1706.03762 (2017)"},{"key":"26_CR31","doi-asserted-by":"crossref","unstructured":"Wang, X., Macdonald, C., Tonellotto, N., Ounis, I.: Pseudo-relevance feedback for multiple representation dense retrieval. arXiv preprint arXiv:2106.11251 (2021)","DOI":"10.1145\/3471158.3472250"},{"key":"26_CR32","doi-asserted-by":"crossref","unstructured":"Wicks, R., Post, M.: A unified approach to sentence segmentation of punctuated text in many languages. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 3995\u20134007. Association for Computational Linguistics, Online, August 2021","DOI":"10.18653\/v1\/2021.acl-long.309"},{"key":"26_CR33","unstructured":"Wolf, T., et al.: Transformers: State-of-the-art natural language processing. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pp. 38\u201345. Association for Computational Linguistics, Online (Oct 2020)"},{"key":"26_CR34","doi-asserted-by":"crossref","unstructured":"Yang, P., Fang, H., Lin, J.: Anserini: enabling the use of Lucene for information retrieval research. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1253\u20131256. SIGIR 2017, Association for Computing Machinery, New York, NY, USA, August 2017","DOI":"10.1145\/3077136.3080721"},{"key":"26_CR35","unstructured":"Yang, W., Zhang, H., Lin, J.: Simple applications of BERT for ad hoc document retrieval. arXiv preprint arXiv:1903.10972 (2019)"},{"key":"26_CR36","doi-asserted-by":"crossref","unstructured":"Yu, P., Allan, J.: A study of neural matching models for cross-lingual IR. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1637\u20131640. Association for Computing Machinery, New York, NY, USA (2020)","DOI":"10.1145\/3397271.3401322"},{"key":"26_CR37","doi-asserted-by":"crossref","unstructured":"Zhang, R., et al.: Improving low-resource cross-lingual document retrieval by reranking with deep bilingual representations. arXiv preprint arXiv:1906.03492 (2019)","DOI":"10.18653\/v1\/P19-1306"},{"key":"26_CR38","doi-asserted-by":"crossref","unstructured":"Zhao, L., Zbib, R., Jiang, Z., Karakos, D., Huang, Z.: Weakly supervised attentional model for low resource ad-hoc cross-lingual information retrieval. In: Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019), pp. 259\u2013264. Association for Computational Linguistics, Hong Kong, China, November 2019","DOI":"10.18653\/v1\/D19-6129"}],"container-title":["Lecture Notes in Computer Science","Advances in Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-99736-6_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T15:42:36Z","timestamp":1726933356000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-99736-6_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030997359","9783030997366"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-99736-6_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"5 April 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Information Retrieval","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Stavanger","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Norway","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 April 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"44","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecir2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecir2022.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"395","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"35","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"29","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"9% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4-6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Additionally, there are other papers: 11 reproducibility, 12 doctoral, 13 CLEF Labs, 5 workshops and 4 tutorials.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}