{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T01:03:31Z","timestamp":1774400611926,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":62,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T00:00:00Z","timestamp":1689638400000},"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":[[2023,7,19]]},"DOI":"10.1145\/3539618.3591740","type":"proceedings-article","created":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T00:22:59Z","timestamp":1689726179000},"page":"163-173","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Multivariate Representation Learning for Information Retrieval"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0800-3340","authenticated-orcid":false,"given":"Hamed","family":"Zamani","sequence":"first","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2941-6240","authenticated-orcid":false,"given":"Michael","family":"Bendersky","sequence":"additional","affiliation":[{"name":"Google Research, Mountain View, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,7,18]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482011"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2020.102248"},{"key":"e_1_3_2_1_4_1","volume-title":"MS MARCO: A Human Generated MAchine Reading COmprehension Dataset. 30th Conference on Neural Information Processing Systems, NIPS","author":"Campos Daniel Fernando","year":"2016","unstructured":"Daniel Fernando Campos, Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, Li Deng, and Bhaskar Mitra. 2016. MS MARCO: A Human Generated MAchine Reading COmprehension Dataset. 30th Conference on Neural Information Processing Systems, NIPS (2016)."},{"key":"e_1_3_2_1_5_1","volume-title":"Estimating the Query Difficulty for Information Retrieval","author":"Carmel David","unstructured":"David Carmel and Elad Yom-Tov. 2010. Estimating the Query Difficulty for Information Retrieval 1st ed.). Morgan and Claypool Publishers.","edition":"1"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390334.1390446"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462951"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277795"},{"key":"e_1_3_2_1_9_1","volume-title":"Overview of the TREC 2019 Deep Learning Track. In TREC.","author":"Craswell Nick","year":"2019","unstructured":"Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2019. Overview of the TREC 2019 Deep Learning Track. In TREC."},{"key":"e_1_3_2_1_10_1","volume-title":"Overview of the TREC 2020 Deep Learning Track. In TREC.","author":"Craswell Nick","year":"2020","unstructured":"Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2020. Overview of the TREC 2020 Deep Learning Track. In TREC."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/564376.564429"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401204"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1"},{"key":"e_1_3_2_1_14_1","volume-title":"international conference on machine learning. PMLR, 1050--1059","author":"Gal Yarin","year":"2016","unstructured":"Yarin Gal and Zoubin Ghahramani. 2016. Dropout as a bayesian approximation: Representing model uncertainty in deep learning. In international conference on machine learning. PMLR, 1050--1059."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1842890.1842906"},{"key":"e_1_3_2_1_16_1","volume-title":"Inferring Query Performance Using Pre-retrieval Predictors","author":"He Ben","unstructured":"Ben He and Iadh Ounis. 2004. Inferring Query Performance Using Pre-retrieval Predictors. In String Processing and Information Retrieval, Alberto Apostolico and Massimo Melucci (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 43--54."},{"key":"e_1_3_2_1_17_1","volume-title":"Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation. ArXiv","author":"Hofst\u00e4tter Sebastian","year":"2020","unstructured":"Sebastian Hofst\u00e4tter, Sophia Althammer, Michael Schr\u00f6der, Mete Sertkan, and Allan Hanbury. 2020. Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation. ArXiv, Vol. abs\/2010.02666 (2020)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462891"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2838931.2838934"},{"key":"e_1_3_2_1_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)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2019.2921572"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.550"},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '20)","author":"Khattab O.","unstructured":"O. Khattab and Matei A. Zaharia. 2020. 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 (SIGIR '20)."},{"key":"e_1_3_2_1_25_1","volume-title":"Proceedings of the 3rd International Conference for Learning Representations (ICLR'15)","author":"Diederik","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In Proceedings of the 3rd International Conference for Learning Representations (ICLR'15)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539137"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/383952.383970"},{"key":"e_1_3_2_1_28_1","volume-title":"Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021)","author":"Lin Sheng-Chieh","year":"2021","unstructured":"Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy J. Lin. 2021. Distilling Dense Representations for Ranking using Tightly-Coupled Teachers. Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021) (2021)."},{"key":"e_1_3_2_1_29_1","volume-title":"WWW'18 Open Challenge: Financial Opinion Mining and Question Answering. WWW '18: Companion Proceedings of the The Web Conference 2018","author":"Maia Macedo","year":"2018","unstructured":"Macedo Maia, Siegfried Handschuh, Andre Freitas, Brian Davis, Ross McDermott, Manel Zarrouk, and Alexandra Balahur. 2018. WWW'18 Open Challenge: Financial Opinion Mining and Question Answering. WWW '18: Companion Proceedings of the The Web Conference 2018, 1941--1942."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2889473"},{"key":"e_1_3_2_1_31_1","volume-title":"Poincar\u00e9 embeddings for learning hierarchical representations. Advances in neural information processing systems","author":"Nickel Maximillian","year":"2017","unstructured":"Maximillian Nickel and Douwe Kiela. 2017. Poincar\u00e9 embeddings for learning hierarchical representations. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_1_32_1","unstructured":"Rodrigo Nogueira. 2019. From doc2query to docTTTTTquery."},{"key":"e_1_3_2_1_33_1","volume-title":"Passage Re-ranking with BERT. ArXiv","author":"Nogueira Rodrigo","year":"2019","unstructured":"Rodrigo Nogueira and Kyunghyun Cho. 2019. Passage Re-ranking with BERT. ArXiv, Vol. abs\/1901.04085 (2019)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.eacl-main.12"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/290941.291008"},{"key":"e_1_3_2_1_36_1","unstructured":"The Lemur Project. [n.d.]. Galago. https:\/\/www.lemurproject.org\/galago.php"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.466"},{"key":"e_1_3_2_1_38_1","first-page":"1","article-title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","volume":"21","author":"Raffel Colin","year":"2020","unstructured":"Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. Journal of Machine Learning Research, Vol. 21, 140 (2020), 1--67. http:\/\/jmlr.org\/papers\/v21\/20-074.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_39_1","volume-title":"Proceedings of the Third Text REtrieval Conference (TREC-3). Gaithersburg, MD: NIST, 109--126","author":"Robertson Stephen","unstructured":"Stephen Robertson, S. Walker, S. Jones, M. M. Hancock-Beaulieu, and M. Gatford. 1995. Okapi at TREC-3. In Proceedings of the Third Text REtrieval Conference (TREC-3). Gaithersburg, MD: NIST, 109--126."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2018.10.009"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/361219.361220"},{"key":"e_1_3_2_1_42_1","volume-title":"a distilled version of BERT: smaller, faster, cheaper and lighter. ArXiv","author":"Sanh Victor","year":"2019","unstructured":"Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019. DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. ArXiv, Vol. abs\/1910.01108 (2019)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.naacl-main.272"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2348283.2348310"},{"key":"e_1_3_2_1_45_1","volume-title":"BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models. In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track.","author":"Thakur Nandan","year":"2021","unstructured":"Nandan Thakur, Nils Reimers, Andreas R\u00fcckl\u00e9, Abhishek Srivastava, and Iryna Gurevych. 2021. BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models. In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track."},{"key":"e_1_3_2_1_46_1","volume-title":"Proceedings of the 2016 International Conference on Learning Representations (ICLR '16)","author":"Vendrov Ivan","year":"2016","unstructured":"Ivan Vendrov, Ryan Kiros, Sanja Fidler, and Raquel Urtasun. 2016. Order-Embeddings of Images and Language. In Proceedings of the 2016 International Conference on Learning Representations (ICLR '16)."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1025"},{"key":"e_1_3_2_1_48_1","volume-title":"Proceedings of the 3rd International Conference on Learning Representations (ICLR '15)","author":"Vilnis Luke","year":"2015","unstructured":"Luke Vilnis and Andrew McCallum. 2015. Word Representations via Gaussian Embedding. In Proceedings of the 3rd International Conference on Learning Representations (ICLR '15), Yoshua Bengio and Yann LeCun (Eds.)."},{"key":"e_1_3_2_1_49_1","volume-title":"Overview of the TREC 2004 Robust Retrieval Track. In The Thirteenth Text REtrieval Conference, TREC 2004. 70--80","author":"Voorhees Ellen M.","year":"2004","unstructured":"Ellen M. Voorhees. 2004. Overview of the TREC 2004 Robust Retrieval Track. In The Thirteenth Text REtrieval Conference, TREC 2004. 70--80."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3451964.3451965"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.609"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1571963"},{"key":"e_1_3_2_1_53_1","volume-title":"Proceedings of the 9th International Conference on Learning Representations (ICLR '21)","author":"Xiong Lee","year":"2021","unstructured":"Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk. 2021. Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. In Proceedings of the 9th International Conference on Learning Representations (ICLR '21)."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210041"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271800"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531722"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531791"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462880"},{"key":"e_1_3_2_1_59_1","volume-title":"Advances in Information Retrieval Theory, Leif Azzopardi, Gabriella Kazai, Stephen Robertson, Stefan R\u00fcger","author":"Zhang Dell","unstructured":"Dell Zhang and Jinsong Lu. 2009. Batch-Mode Computational Advertising Based on Modern Portfolio Theory. In Advances in Information Retrieval Theory, Leif Azzopardi, Gabriella Kazai, Stephen Robertson, Stefan R\u00fcger, Milad Shokouhi, Dawei Song, and Emine Yilmaz (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 380--383."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.5555\/1793274.1793285"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.443"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-00958-7_5"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835449.1835600"}],"event":{"name":"SIGIR '23: The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Taipei Taiwan","acronym":"SIGIR '23","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3539618.3591740","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3539618.3591740","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:47:01Z","timestamp":1750178821000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3539618.3591740"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,18]]},"references-count":62,"alternative-id":["10.1145\/3539618.3591740","10.1145\/3539618"],"URL":"https:\/\/doi.org\/10.1145\/3539618.3591740","relation":{},"subject":[],"published":{"date-parts":[[2023,7,18]]},"assertion":[{"value":"2023-07-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}