{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T05:18:55Z","timestamp":1784179135827,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,7,11]],"date-time":"2021-07-11T00:00:00Z","timestamp":1625961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,7,11]]},"DOI":"10.1145\/3404835.3462812","type":"proceedings-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T03:08:25Z","timestamp":1626059305000},"page":"2666-2668","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Pretrained Transformers for Text Ranking: BERT and Beyond"],"prefix":"10.1145","author":[{"given":"Andrew","family":"Yates","sequence":"first","affiliation":[{"name":"Max Planck Institute for Informatics, Saarbruecken, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rodrigo","family":"Nogueira","sequence":"additional","affiliation":[{"name":"University of Waterloo, Waterloo, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jimmy","family":"Lin","sequence":"additional","affiliation":[{"name":"University of Waterloo, Waterloo, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,7,11]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1352"},{"key":"e_1_3_2_1_2_1","volume-title":"Language Models are Few-Shot Learners. arXiv:2005.14165","author":"Brown Tom B.","year":"2020","unstructured":"Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020. Language Models are Few-Shot Learners. arXiv:2005.14165 (2020)."},{"key":"e_1_3_2_1_3_1","volume-title":"2019 a. Context-Aware Sentence\/Passage Term Importance Estimation For First Stage Retrieval. arXiv:1910.10687","author":"Dai Zhuyun","year":"2019","unstructured":"Zhuyun Dai and Jamie Callan. 2019 a. Context-Aware Sentence\/Passage Term Importance Estimation For First Stage Retrieval. arXiv:1910.10687 (2019)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331303"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380258"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2016.06.012"},{"key":"e_1_3_2_1_7_1","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","volume":"1","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. 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). Minneapolis, Minnesota, 4171--4186."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.134"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3409256.3409838"},{"key":"e_1_3_2_1_10_1","volume-title":"2020 b. Complementing Lexical Retrieval with Semantic Residual Embedding. arXiv:2004.13969","author":"Gao Luyu","year":"2020","unstructured":"Luyu Gao, Zhuyun Dai, Zhen Fan, and Jamie Callan. 2020 b. Complementing Lexical Retrieval with Semantic Residual Embedding. arXiv:2004.13969 (2020)."},{"key":"e_1_3_2_1_11_1","volume-title":"Laszlo Lukacs, Ruiqi Guo, Sanjiv Kumar, Balint Miklos, and Ray Kurzweil.","author":"Henderson Matthew","year":"2017","unstructured":"Matthew Henderson, Rami Al-Rfou, Brian Strope, Yun hsuan Sung, Laszlo Lukacs, Ruiqi Guo, Sanjiv Kumar, Balint Miklos, and Ray Kurzweil. 2017. Efficient Natural Language Response Suggestion for Smart Reply. arXiv:1705.00652 (2017)."},{"key":"e_1_3_2_1_12_1","volume-title":"2020 a. Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation. arXiv:2010.02666","author":"Sebastian","year":"2020","unstructured":"Sebastian Hofst\"atter, Sophia Althammer, Michael Schr\u00f6der, Mete Sertkan, and Allan Hanbury. 2020 a. Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation. arXiv:2010.02666 (2020)."},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the 44th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021)","author":"Sebastian","year":"2021","unstructured":"Sebastian Hofst\"atter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, and Allan Hanbury. 2021. Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling. In Proceedings of the 44th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021) ."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 24th European Conference on Artificial Intelligence (ECAI","author":"Sebastian","year":"2020","unstructured":"Sebastian Hofst\"atter, Markus Zlabinger, and Allan Hanbury. 2020 b. Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking. In Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020). Santiago de Compostela, Spain."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505665"},{"key":"e_1_3_2_1_16_1","volume-title":"Proceedings of the 8th International Conference on Learning Representations (ICLR 2020)","author":"Humeau Samuel","year":"2020","unstructured":"Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston. 2020. Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring. In Proceedings of the 8th International Conference on Learning Representations (ICLR 2020) ."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.550"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401075"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1612"},{"key":"e_1_3_2_1_20_1","volume-title":"PARADE: Passage Representation Aggregation for Document Reranking. arXiv:2008.09093","author":"Li Canjia","year":"2020","unstructured":"Canjia Li, Andrew Yates, Sean MacAvaney, Ben He, and Yingfei Sun. 2020. PARADE: Passage Representation Aggregation for Document Reranking. arXiv:2008.09093 (2020)."},{"key":"e_1_3_2_1_21_1","volume-title":"2020 a. Pretrained Transformers for Text Ranking: BERT and Beyond. arXiv:2010.06467","author":"Lin Jimmy","year":"2020","unstructured":"Jimmy Lin, Rodrigo Nogueira, and Andrew Yates. 2020 a. Pretrained Transformers for Text Ranking: BERT and Beyond. arXiv:2010.06467 (2020)."},{"key":"e_1_3_2_1_22_1","volume-title":"2020 b. Distilling Dense Representations for Ranking using Tightly-Coupled Teachers. arXiv:2010.11386","author":"Lin Sheng-Chieh","year":"2020","unstructured":"Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. 2020 b. Distilling Dense Representations for Ranking using Tightly-Coupled Teachers. arXiv:2010.11386 (2020)."},{"key":"e_1_3_2_1_23_1","volume-title":"TwinBERT: Distilling Knowledge to Twin-Structured BERT Models for Efficient Retrieval. arXiv:2002.06275","author":"Lu Wenhao","year":"2020","unstructured":"Wenhao Lu, Jian Jiao, and Ruofei Zhang. 2020. TwinBERT: Distilling Knowledge to Twin-Structured BERT Models for Efficient Retrieval. arXiv:2002.06275 (2020)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401262"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331317"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401266"},{"key":"e_1_3_2_1_27_1","volume-title":"Advances in Neural Information Processing Systems 26 (NIPS","author":"Mikolov Tomas","year":"2013","unstructured":"Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S. Corrado, and Jeff Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. In Advances in Neural Information Processing Systems 26 (NIPS 2013). Lake Tahoe, California, 3111--3119."},{"key":"e_1_3_2_1_28_1","volume-title":"Conformer-Kernel with Query Term Independence for Document Retrieval. arXiv:2007.10434","author":"Mitra Bhaskar","year":"2020","unstructured":"Bhaskar Mitra, Sebastian Hofstatter, Hamed Zamani, and Nick Craswell. 2020. Conformer-Kernel with Query Term Independence for Document Retrieval. arXiv:2007.10434 (2020)."},{"key":"e_1_3_2_1_29_1","volume-title":"A Dual Embedding Space Model for Document Ranking. arXiv:1602.01137v1","author":"Mitra Bhaskar","year":"2016","unstructured":"Bhaskar Mitra, Eric Nalisnick, Nick Craswell, and Rich Caruana. 2016. A Dual Embedding Space Model for Document Ranking. arXiv:1602.01137v1 (2016)."},{"key":"e_1_3_2_1_30_1","volume-title":"Passage Re-ranking with BERT. arXiv:1901.04085","author":"Nogueira Rodrigo","year":"2019","unstructured":"Rodrigo Nogueira and Kyunghyun Cho. 2019. Passage Re-ranking with BERT. arXiv:1901.04085 (2019)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.63"},{"key":"e_1_3_2_1_32_1","unstructured":"Rodrigo Nogueira and Jimmy Lin. 2019. From doc2query to docTTTTTquery. (2019)."},{"key":"e_1_3_2_1_33_1","unstructured":"Rodrigo Nogueira Wei Yang Kyunghyun Cho and Jimmy Lin. 2019 a. Multi-Stage Document Ranking with BERT. In arXiv:1910.14424 ."},{"key":"e_1_3_2_1_34_1","unstructured":"Rodrigo Nogueira Wei Yang Jimmy Lin and Kyunghyun Cho. 2019 b. Document Expansion by Query Prediction. In arXiv:1904.08375 ."},{"key":"e_1_3_2_1_35_1","volume-title":"RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering. arXiv:2010.08191","author":"Qu Yingqi","year":"2020","unstructured":"Yingqi Qu, Yuchen Ding, Jing Liu, Kai Liu, Ruiyang Ren, Xin Zhao, Daxiang Dong, Hua Wu, and Haifeng Wang. 2020. RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering. arXiv:2010.08191 (2020)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.504"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11996"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380305"},{"key":"e_1_3_2_1_40_1","volume-title":"Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. arXiv:2007.00808","author":"Xiong Lee","year":"2020","unstructured":"Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk. 2020. Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. arXiv:2007.00808 (2020)."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271800"},{"key":"e_1_3_2_1_42_1","volume-title":"RepBERT: Contextualized Text Embeddings for First-Stage Retrieval. arXiv:2006.15498","author":"Zhan Jingtao","year":"2020","unstructured":"Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, and Shaoping Ma. 2020. RepBERT: Contextualized Text Embeddings for First-Stage Retrieval. arXiv:2006.15498 (2020)."}],"event":{"name":"SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Virtual Event Canada","acronym":"SIGIR '21","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404835.3462812","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3404835.3462812","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:16Z","timestamp":1750193236000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404835.3462812"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,11]]},"references-count":42,"alternative-id":["10.1145\/3404835.3462812","10.1145\/3404835"],"URL":"https:\/\/doi.org\/10.1145\/3404835.3462812","relation":{},"subject":[],"published":{"date-parts":[[2021,7,11]]},"assertion":[{"value":"2021-07-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}