{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:22:46Z","timestamp":1785543766652,"version":"3.56.0"},"publisher-location":"New York, NY, USA","reference-count":51,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T00:00:00Z","timestamp":1657065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Natural Science Foundation of China","award":["61732008, 61902209"],"award-info":[{"award-number":["61732008, 61902209"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,7,6]]},"DOI":"10.1145\/3477495.3531943","type":"proceedings-article","created":{"date-parts":[[2022,7,7]],"date-time":"2022-07-07T15:12:08Z","timestamp":1657206728000},"page":"1524-1534","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Axiomatically Regularized Pre-training for Ad hoc Search"],"prefix":"10.1145","author":[{"given":"Jia","family":"Chen","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiqun","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Fang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaxin","family":"Mao","sequence":"additional","affiliation":[{"name":"Renmin University of China, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Fang","sequence":"additional","affiliation":[{"name":"University of Delaware, Newark, DE, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shenghao","family":"Yang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohui","family":"Xie","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoping","family":"Ma","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,7,7]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582416"},{"key":"e_1_3_2_1_2_1","volume-title":"Investigating Retrieval Method Selection with Axiomatic Features. arXiv preprint arXiv:1904.05737","author":"Arora Siddhant","year":"2019","unstructured":"Siddhant Arora and Andrew Yates . 2019. Investigating Retrieval Method Selection with Axiomatic Features. arXiv preprint arXiv:1904.05737 ( 2019 ). Siddhant Arora and Andrew Yates. 2019. Investigating Retrieval Method Selection with Axiomatic Features. arXiv preprint arXiv:1904.05737 (2019)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-45439-5_40"},{"key":"e_1_3_2_1_4_1","volume-title":"Pre-training tasks for embedding-based large-scale retrieval. arXiv preprint arXiv:2002.03932","author":"Chang Wei-Cheng","year":"2020","unstructured":"Wei-Cheng Chang , Felix X Yu , Yin-Wen Chang , Yiming Yang , and Sanjiv Kumar . 2020. Pre-training tasks for embedding-based large-scale retrieval. arXiv preprint arXiv:2002.03932 ( 2020 ). Wei-Cheng Chang, Felix X Yu, Yin-Wen Chang, Yiming Yang, and Sanjiv Kumar. 2020. Pre-training tasks for embedding-based large-scale retrieval. arXiv preprint arXiv:2002.03932 (2020)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3448127","article-title":"A Hybrid Framework for Session Context Modeling","volume":"39","author":"Chen Jia","year":"2021","unstructured":"Jia Chen , Jiaxin Mao , Yiqun Liu , Ziyi Ye , Weizhi Ma , Chao Wang , Min Zhang , and Shaoping Ma . 2021 . A Hybrid Framework for Session Context Modeling . ACM Transactions on Information Systems (TOIS) 39 , 3 (2021), 1 -- 35 . Jia Chen, Jiaxin Mao, Yiqun Liu, Ziyi Ye, Weizhi Ma, Chao Wang, Min Zhang, and Shaoping Ma. 2021. A Hybrid Framework for Session Context Modeling. ACM Transactions on Information Systems (TOIS) 39, 3 (2021), 1--35.","journal-title":"ACM Transactions on Information Systems (TOIS)"},{"key":"e_1_3_2_1_6_1","volume-title":"Toward the Understanding of Deep Text Matching Models for Information Retrieval. arXiv preprint arXiv:2108.07081","author":"Chen Lijuan","year":"2021","unstructured":"Lijuan Chen , Yanyan Lan , Liang Pang , Jiafeng Guo , and Xueqi Cheng . 2021. Toward the Understanding of Deep Text Matching Models for Information Retrieval. arXiv preprint arXiv:2108.07081 ( 2021 ). Lijuan Chen, Yanyan Lan, Liang Pang, Jiafeng Guo, and Xueqi Cheng. 2021. Toward the Understanding of Deep Text Matching Models for Information Retrieval. arXiv preprint arXiv:2108.07081 (2021)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3409256.3409828"},{"key":"e_1_3_2_1_9_1","volume-title":"Overview of the trec 2019 deep learning track. arXiv preprint arXiv:2003.07820","author":"Craswell Nick","year":"2020","unstructured":"Nick Craswell , Bhaskar Mitra , Emine Yilmaz , Daniel Campos , and Ellen M Voorhees . 2020. Overview of the trec 2019 deep learning track. arXiv preprint arXiv:2003.07820 ( 2020 ). Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M Voorhees. 2020. Overview of the trec 2019 deep learning track. arXiv preprint arXiv:2003.07820 (2020)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159659"},{"key":"e_1_3_2_1_11_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018). Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_12_1","unstructured":"Yixing Fan Xiaohui Xie Yinqiong Cai Jia Chen Xinyu Ma Xiangsheng Li Ruqing Zhang Jiafeng Guo and Yiqun Liu. 2021. Pre-training Methods in Information Retrieval. arXiv:cs.IR\/2111.13853  Yixing Fan Xiaohui Xie Yinqiong Cai Jia Chen Xinyu Ma Xiangsheng Li Ruqing Zhang Jiafeng Guo and Yiqun Liu. 2021. Pre-training Methods in Information Retrieval. arXiv:cs.IR\/2111.13853"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1008992.1009004"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1961209.1961210"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148193"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.75"},{"key":"e_1_3_2_1_17_1","volume-title":"Unsupervised corpus aware language model pre-training for dense passage retrieval. arXiv preprint arXiv:2108.05540","author":"Gao Luyu","year":"2021","unstructured":"Luyu Gao and Jamie Callan . 2021. Unsupervised corpus aware language model pre-training for dense passage retrieval. arXiv preprint arXiv:2108.05540 ( 2021 ). Luyu Gao and Jamie Callan. 2021. Unsupervised corpus aware language model pre-training for dense passage retrieval. arXiv preprint arXiv:2108.05540 (2021)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1526709.1526761"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983769"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983704"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401075"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331205"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2661829.2661907"},{"key":"e_1_3_2_1_24_1","unstructured":"Ilya Loshchilov and Frank Hutter. 2018. Fixing weight decay regularization in adam. (2018).  Ilya Loshchilov and Frank Hutter. 2018. Fixing weight decay regularization in adam. (2018)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2063576.2063584"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441777"},{"key":"e_1_3_2_1_27_1","volume-title":"B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc Retrieval. arXiv preprint arXiv:2104.09791","author":"Ma Xinyu","year":"2021","unstructured":"Xinyu Ma , Jiafeng Guo , Ruqing Zhang , Yixing Fan , Yingyan Li , and Xueqi Cheng . 2021. B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc Retrieval. arXiv preprint arXiv:2104.09791 ( 2021 ). Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Yingyan Li, and Xueqi Cheng. 2021. B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc Retrieval. arXiv preprint arXiv:2104.09791 (2021)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482286"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331317"},{"key":"e_1_3_2_1_30_1","volume-title":"MS MARCO: A human generated machine reading comprehension dataset. In CoCo@ NIPS.","author":"Nguyen Tri","year":"2016","unstructured":"Tri Nguyen , Mir Rosenberg , Xia Song , Jianfeng Gao , Saurabh Tiwary , Rangan Majumder , and Li Deng . 2016 . MS MARCO: A human generated machine reading comprehension dataset. In CoCo@ NIPS. Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 2016. MS MARCO: A human generated machine reading comprehension dataset. In CoCo@ NIPS."},{"key":"e_1_3_2_1_31_1","first-page":"297","article-title":"Rethinking query expansion for bert reranking","volume":"12036","author":"Padaki Ramith","year":"2020","unstructured":"Ramith Padaki , Zhuyun Dai , and Jamie Callan . 2020 . Rethinking query expansion for bert reranking . Advances in Information Retrieval 12036 (2020), 297 . Ramith Padaki, Zhuyun Dai, and Jamie Callan. 2020. Rethinking query expansion for bert reranking. Advances in Information Retrieval 12036 (2020), 297.","journal-title":"Advances in Information Retrieval"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"e_1_3_2_1_33_1","volume-title":"arXiv preprint arXiv:1306.2597","author":"Qin Tao","year":"2013","unstructured":"Tao Qin and Tie-Yan Liu . 2013. Introducing LETOR 4.0 datasets. arXiv preprint arXiv:1306.2597 ( 2013 ). Tao Qin and Tie-Yan Liu. 2013. Introducing LETOR 4.0 datasets. arXiv preprint arXiv:1306.2597 (2013)."},{"key":"e_1_3_2_1_34_1","unstructured":"Alec Radford Karthik Narasimhan Tim Salimans and Ilya Sutskever. 2018. Improving language understanding by generative pre-training. (2018).  Alec Radford Karthik Narasimhan Tim Salimans and Ilya Sutskever. 2018. Improving language understanding by generative pre-training. (2018)."},{"key":"e_1_3_2_1_35_1","volume-title":"The probabilistic relevance framework: BM25 and beyond","author":"Robertson Stephen","unstructured":"Stephen Robertson and Hugo Zaragoza . 2009. The probabilistic relevance framework: BM25 and beyond . Now Publishers Inc . Stephen Robertson and Hugo Zaragoza. 2009. The probabilistic relevance framework: BM25 and beyond. Now Publishers Inc."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331296"},{"key":"e_1_3_2_1_37_1","volume-title":"Simple entity-centric questions challenge dense retrievers. arXiv preprint arXiv:2109.08535","author":"Sciavolino Christopher","year":"2021","unstructured":"Christopher Sciavolino , Zexuan Zhong , Jinhyuk Lee , and Danqi Chen . 2021. Simple entity-centric questions challenge dense retrievers. arXiv preprint arXiv:2109.08535 ( 2021 ). Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, and Danqi Chen. 2021. Simple entity-centric questions challenge dense retrievers. arXiv preprint arXiv:2109.08535 (2021)."},{"key":"e_1_3_2_1_38_1","volume-title":"International Conference on Machine Learning. PMLR, 3319-- 3328","author":"Sundararajan Mukund","year":"2017","unstructured":"Mukund Sundararajan , Ankur Taly , and Qiqi Yan . 2017 . Axiomatic attribution for deep networks . In International Conference on Machine Learning. PMLR, 3319-- 3328 . Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017. Axiomatic attribution for deep networks. In International Conference on Machine Learning. PMLR, 3319-- 3328."},{"key":"e_1_3_2_1_39_1","volume-title":"ukasz Kaiser, and Illia Polosukhin","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani , Noam Shazeer , Niki Parmar , Jakob Uszkoreit , Llion Jones , Aidan N Gomez , ukasz Kaiser, and Illia Polosukhin . 2017 . Attention is all you need. In Advances in neural information processing systems. 5998--6008. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3471158.3472256"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/1067268.1067272"},{"key":"e_1_3_2_1_42_1","unstructured":"Lucy Lu Wang Kyle Lo Yoganand Chandrasekhar Russell Reas Jiangjiang Yang Darrin Eide Kathryn Funk Rodney Kinney Ziyang Liu William Merrill etal 2020. Cord-19: The covid-19 open research dataset. ArXiv (2020).  Lucy Lu Wang Kyle Lo Yoganand Chandrasekhar Russell Reas Jiangjiang Yang Darrin Eide Kathryn Funk Rodney Kinney Ziyang Liu William Merrill et al. 2020. Cord-19: The covid-19 open research dataset. ArXiv (2020)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-28997-2_10"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080809"},{"key":"e_1_3_2_1_45_1","volume-title":"Approximate nearest neighbor negative contrastive learning for dense text retrieval. arXiv preprint 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 preprint arXiv:2007.00808 ( 2020 ). 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 preprint arXiv:2007.00808 (2020)."},{"key":"e_1_3_2_1_46_1","volume-title":"Simple applications of BERT for ad hoc document retrieval. arXiv preprint arXiv:1903.10972","author":"Yang Wei","year":"2019","unstructured":"Wei Yang , Haotian Zhang , and Jimmy Lin . 2019. Simple applications of BERT for ad hoc document retrieval. arXiv preprint arXiv:1903.10972 ( 2019 ). Wei Yang, Haotian Zhang, and Jimmy Lin. 2019. Simple applications of BERT for ad hoc document retrieval. arXiv preprint arXiv:1903.10972 (2019)."},{"key":"e_1_3_2_1_47_1","volume-title":"Xlnet: Generalized autoregressive pretraining for language understanding. Advances in neural information processing systems 32","author":"Yang Zhilin","year":"2019","unstructured":"Zhilin Yang , Zihang Dai , Yiming Yang , Jaime Carbonell , Russ R Salakhutdinov , and Quoc V Le . 2019 . Xlnet: Generalized autoregressive pretraining for language understanding. Advances in neural information processing systems 32 (2019). Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 2019. Xlnet: Generalized autoregressive pretraining for language understanding. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_1_48_1","volume-title":"Statistical language models for information retrieval. Synthesis lectures on human language technologies 1, 1","author":"Zhai ChengXiang","year":"2008","unstructured":"ChengXiang Zhai . 2008. Statistical language models for information retrieval. Synthesis lectures on human language technologies 1, 1 ( 2008 ), 1--141. ChengXiang Zhai. 2008. Statistical language models for information retrieval. Synthesis lectures on human language technologies 1, 1 (2008), 1--141."},{"key":"e_1_3_2_1_49_1","volume-title":"Optimizing Dense Retrieval Model Training with Hard Negatives. arXiv preprint arXiv:2104.08051","author":"Zhan Jingtao","year":"2021","unstructured":"Jingtao Zhan , Jiaxin Mao , Yiqun Liu , Jiafeng Guo , Min Zhang , and Shaoping Ma. 2021. Optimizing Dense Retrieval Model Training with Hard Negatives. arXiv preprint arXiv:2104.08051 ( 2021 ). Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, and Shaoping Ma. 2021. Optimizing Dense Retrieval Model Training with Hard Negatives. arXiv preprint arXiv:2104.08051 (2021)."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-12275-0_31"},{"key":"e_1_3_2_1_51_1","volume-title":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management. 2749--2758","author":"Zhou Yujia","year":"2021","unstructured":"Yujia Zhou , Zhicheng Dou , Yutao Zhu , and Ji-Rong Wen . 2021 . PSSL: Selfsupervised Learning for Personalized Search with Contrastive Sampling . In Proceedings of the 30th ACM International Conference on Information & Knowledge Management. 2749--2758 . Yujia Zhou, Zhicheng Dou, Yutao Zhu, and Ji-Rong Wen. 2021. PSSL: Selfsupervised Learning for Personalized Search with Contrastive Sampling. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management. 2749--2758."}],"event":{"name":"SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Madrid Spain","acronym":"SIGIR '22","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3477495.3531943","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3477495.3531943","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:19Z","timestamp":1750183819000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3477495.3531943"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,6]]},"references-count":51,"alternative-id":["10.1145\/3477495.3531943","10.1145\/3477495"],"URL":"https:\/\/doi.org\/10.1145\/3477495.3531943","relation":{},"subject":[],"published":{"date-parts":[[2022,7,6]]},"assertion":[{"value":"2022-07-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}