{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T22:51:45Z","timestamp":1776898305040,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":72,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,11,26]],"date-time":"2023-11-26T00:00:00Z","timestamp":1700956800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EU Horizon 2020 ITN\/ETN","award":["H2020-EU.1.3.1., ID: 860721"],"award-info":[{"award-number":["H2020-EU.1.3.1., ID: 860721"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,11,26]]},"DOI":"10.1145\/3624918.3625333","type":"proceedings-article","created":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T08:49:17Z","timestamp":1700729357000},"page":"139-149","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9134-3815","authenticated-orcid":false,"given":"Sophia","family":"Althammer","sequence":"first","affiliation":[{"name":"Information System Engineering, TU Wien, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0271-5563","authenticated-orcid":false,"given":"Guido","family":"Zuccon","sequence":"additional","affiliation":[{"name":"ITEE, The University of Queensland, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1229-2612","authenticated-orcid":false,"given":"Sebastian","family":"Hofst\u00e4tter","sequence":"additional","affiliation":[{"name":"Cohere, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9609-9505","authenticated-orcid":false,"given":"Suzan","family":"Verberne","sequence":"additional","affiliation":[{"name":"LIACS, Leiden University, Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7149-5843","authenticated-orcid":false,"given":"Allan","family":"Hanbury","sequence":"additional","affiliation":[{"name":"TU Wien, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,11,26]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557714"},{"key":"e_1_3_2_1_2_1","volume-title":"Deep batch active learning by diverse, uncertain gradient lower bounds. arXiv preprint arXiv:1906.03671","author":"Ash T","year":"2019","unstructured":"Jordan\u00a0T Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, and Alekh Agarwal. 2019. Deep batch active learning by diverse, uncertain gradient lower bounds. arXiv preprint arXiv:1906.03671 (2019)."},{"key":"e_1_3_2_1_3_1","volume-title":"Proc. of NIPS.","author":"Bajaj Payal","year":"2016","unstructured":"Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew Mcnamara, Bhaskar Mitra, and Tri Nguyen. 2016. MS MARCO : A Human Generated MAchine Reading COmprehension Dataset. In Proc. of NIPS."},{"key":"e_1_3_2_1_4_1","volume-title":"ech Report","author":"Burges JC","year":"2010","unstructured":"Christopher\u00a0JC Burges. 2010. From ranknet to lambdarank to lambdamart: An overview. MSR-Tech Report (2010)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2009916.2009935"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","unstructured":"Aleksandr Chuklin Ilya Markov and Maarten de Rijke. 2015. Click Models for Web Search. Morgan & Claypool. https:\/\/doi.org\/10.2200\/S00654ED1V01Y201507ICR043","DOI":"10.2200\/S00654ED1V01Y201507ICR043"},{"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":"10.5555\/1622737.1622744"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277795"},{"key":"e_1_3_2_1_10_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_11_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_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462804"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463249"},{"key":"e_1_3_2_1_14_1","volume-title":"Information retrieval: Uncertainty and logics: Uncertainty and logics: Advanced models for the representation and retrieval of information. Vol.\u00a04","author":"Crestani Fabio","unstructured":"Fabio Crestani, Mounia Lalmas, and Cornelis\u00a0Joost van Rijsbergen. 1998. Information retrieval: Uncertainty and logics: Uncertainty and logics: Advanced models for the representation and retrieval of information. Vol.\u00a04. Springer Science & Business Media."},{"key":"e_1_3_2_1_15_1","volume-title":"The Eleventh International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=gmL46YMpu2J","author":"Dai Zhuyun","year":"2023","unstructured":"Zhuyun Dai, Vincent\u00a0Y Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith Hall, and Ming-Wei Chang. 2023. Promptagator: Few-shot Dense Retrieval From 8 Examples. In The Eleventh International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=gmL46YMpu2J"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1423"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","unstructured":"Pinar Donmez and Jaime\u00a0G. Carbonell. 2008. Optimizing estimated loss reduction for active sampling in rank learning. In ICML. 248\u2013255. https:\/\/doi.org\/10.1145\/1390156.1390188","DOI":"10.1145\/1390156.1390188"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-00958-7_10"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.638"},{"key":"e_1_3_2_1_20_1","volume-title":"SPLADE v2: Sparse lexical and expansion model for information retrieval. arXiv preprint arXiv:2109.10086","author":"Formal Thibault","year":"2021","unstructured":"Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and St\u00e9phane Clinchant. 2021. SPLADE v2: Sparse lexical and expansion model for information retrieval. arXiv preprint arXiv:2109.10086 (2021)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463098"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007330508534"},{"key":"e_1_3_2_1_23_1","volume-title":"How Train\u2013Test Leakage Affects Zero-Shot Retrieval","author":"Fr\u00f6be Maik","unstructured":"Maik Fr\u00f6be, Christopher Akiki, Martin Potthast, and Matthias Hagen. 2022. How Train\u2013Test Leakage Affects Zero-Shot Retrieval. In String Processing and Information Retrieval, Diego Arroyuelo and Barbara Poblete (Eds.). Springer International Publishing, Cham, 147\u2013161."},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the 33rd International Conference on International Conference on Machine Learning -","volume":"48","author":"Gal Yarin","year":"2016","unstructured":"Yarin Gal and Zoubin Ghahramani. 2016. Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. In Proceedings of the 33rd International Conference on International Conference on Machine Learning - Volume 48 (New York, NY, USA) (ICML\u201916). JMLR.org, 1050\u20131059."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.75"},{"key":"e_1_3_2_1_26_1","first-page":"11","article-title":"Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review","volume":"17","author":"Grossman R.","year":"2011","unstructured":"Maura\u00a0R. Grossman and Gordon\u00a0V. Cormack. 2011. Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review. Richmond Journal of Law and Technology 17 (2011), 11.","journal-title":"Richmond Journal of Law and Technology"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531832"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-99739-7_17"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462891"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531786"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2019.2921572"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.550"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401075"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3471158.3472229"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-335-6.50026-X"},{"key":"e_1_3_2_1_36_1","volume-title":"Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval","author":"D.","unstructured":"David\u00a0D. Lewis and William\u00a0A. Gale. 1994. A Sequential Algorithm for Training Text Classifiers. In Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Dublin, Ireland) (SIGIR \u201994). Springer-Verlag, Berlin, Heidelberg, 3\u201312."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-02181-7"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2365785"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2889473"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.51"},{"key":"e_1_3_2_1_41_1","unstructured":"Gordon V.\u00a0Cormack Maura R.\u00a0Grossman and Adam Roegiest. 2016. Trec 2016 total recall track overview. In TREC."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463093"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","unstructured":"Rodrigo Nogueira and Kyunghyun Cho. 2019. Passage Re-ranking with BERT. (2019). https:\/\/doi.org\/10.48550\/ARXIV.1901.04085","DOI":"10.48550\/ARXIV.1901.04085"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.63"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463242"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","unstructured":"Nima Sadri and Gordon\u00a0V. Cormack. 2022. Continuous Active Learning Using Pretrained Transformers. (2022). https:\/\/doi.org\/10.48550\/ARXIV.2208.06955","DOI":"10.48550\/ARXIV.2208.06955"},{"key":"e_1_3_2_1_47_1","volume-title":"a distilled version of BERT: smaller, faster, cheaper and lighter. arXiv preprint arXiv:1910.01108","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 preprint arXiv:1910.01108 (2019)."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531766"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/130385.130417"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/1076034.1076047"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/1076034.1076047"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1002\/asi.22958"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.28"},{"key":"e_1_3_2_1_54_1","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 (Round 2). https:\/\/openreview.net\/forum?id=wCu6T5xFjeJ"},{"key":"e_1_3_2_1_55_1","volume-title":"Lecture Notes on Neural Information Retrieval. arXiv preprint arXiv:2207.13443","author":"Tonellotto Nicola","year":"2022","unstructured":"Nicola Tonellotto. 2022. Lecture Notes on Neural Information Retrieval. arXiv preprint arXiv:2207.13443 (2022)."},{"key":"e_1_3_2_1_56_1","volume-title":"Uncertainty in information retrieval systems. Uncertainty management in information systems: from needs to solutions","author":"Turtle R","year":"1997","unstructured":"Howard\u00a0R Turtle and W\u00a0Bruce Croft. 1997. Uncertainty in information retrieval systems. Uncertainty management in information systems: from needs to solutions (1997), 189\u2013224."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1571963"},{"key":"e_1_3_2_1_58_1","volume-title":"Proceedings of NAACL","author":"Wang Kexin","year":"2021","unstructured":"Kexin Wang, Nandan Thakur, Nils Reimers, and Iryna Gurevych. 2021. GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval. In Proceedings of NAACL 2021."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3572960.3572980"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-acl.316"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.5555\/1763653.1763684"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3469096.3469872"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-99736-6_34"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1572112"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/1081870.1081911"},{"key":"e_1_3_2_1_66_1","volume-title":"AcTune: Uncertainty-aware Active Self-Training for Semi-Supervised Active Learning with Pretrained Language Models. arXiv preprint arXiv:2112.08787","author":"Yu Yue","year":"2021","unstructured":"Yue Yu, Lingkai Kong, Jieyu Zhang, Rongzhi Zhang, and Chao Zhang. 2021. AcTune: Uncertainty-aware Active Self-Training for Semi-Supervised Active Learning with Pretrained Language Models. arXiv preprint arXiv:2112.08787 (2021)."},{"key":"e_1_3_2_1_67_1","volume-title":"Cold-start active learning through self-supervised language modeling. arXiv preprint arXiv:2010.09535","author":"Yuan Michelle","year":"2020","unstructured":"Michelle Yuan, Hsuan-Tien Lin, and Jordan Boyd-Graber. 2020. Cold-start active learning through self-supervised language modeling. arXiv preprint arXiv:2010.09535 (2020)."},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","unstructured":"Jingtao Zhan Xiaohui Xie Jiaxin Mao Yiqun Liu Jiafeng Guo Min Zhang and Shaoping Ma. 2022. Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models. (2022). https:\/\/doi.org\/10.48550\/ARXIV.2204.11447","DOI":"10.48550\/ARXIV.2204.11447"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.sustainlp-1.14"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.3115\/1599081.1599224"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1571961"},{"key":"e_1_3_2_1_72_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04417-5_21"}],"event":{"name":"SIGIR-AP '23: Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","location":"Beijing China","acronym":"SIGIR-AP '23","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3624918.3625333","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3624918.3625333","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T21:32:44Z","timestamp":1755898364000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3624918.3625333"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,26]]},"references-count":72,"alternative-id":["10.1145\/3624918.3625333","10.1145\/3624918"],"URL":"https:\/\/doi.org\/10.1145\/3624918.3625333","relation":{},"subject":[],"published":{"date-parts":[[2023,11,26]]},"assertion":[{"value":"2023-11-26","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}