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The advent of deep neural networks pre-trained via language modeling tasks has spurred a number of successful applications in natural language processing.
Rodrigo Nogueira and Kyunghyun Cho. 2019 · 1901
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SciBERT: Pretrained contextualized embeddings for scientific text
Iz Beltagy, Arman Cohan, and Kyle Lo. 2019 · 1903
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Simple applications of BERT for ad hoc document retrieval
Wei Yang, Haotian Zhang, and Jimmy Lin. 2019c · 1903
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019 · 1910
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Okapi at TREC-3
Stephen E. Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford. 1994 · 1994
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Condorcet fusion for improved retrieval
Mark Montague and Javed A. Aslam. 2002 · 2002
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The philosophy of information retrieval evaluation
Ellen M. Voorhees. 2002 · 2002
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Robust real-time face detection
Paul Viola and Michael J. Jones. 2004 · 2004
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High accuracy retrieval with multiple nested ranker
Irina Matveeva, Chris Burges, Timo Burkard, Andy Laucius, and Leon Wong. 2006 · 2006
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Reciprocal rank fusion outperforms Condorcet and individual rank learning methods
Gordon V. Cormack, Charles L. A. Clarke, and Stefan Büttcher. 2009 · 2009
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Learning to rank for information retrieval
Tie-Yan Liu. 2009 · 2009
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Early exit optimizations for additive machine learned ranking systems
B. Barla Cambazoglu, Hugo Zaragoza, Olivier Chapelle, Jiang Chen, Ciya Liao, Zhaohui Zheng, and Jon Degenhardt. 2010 · 2010
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Query understanding at Bing
Jan Pedersen. 2010 · 2010
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Learning to Rank for Information Retrieval and Natural Language Processing
Hang Li. 2011 · 2011
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A cascade ranking model for efficient ranked retrieval
Lidan Wang, Jimmy Lin, and Donald Metzler. 2011 · 2011
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The greedy miser: Learning under test-time budgets
Zhixiang Eddie Xu, Kilian Q. Weinberger, and Olivier Chapelle. 2012 · 2012
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Effectiveness/efficiency tradeoffs for candidate generation in multi-stage retrieval architectures
Nima Asadi and Jimmy Lin. 2013 · 2013
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
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Old dogs are great at new tricks: Column stores for IR prototyping
Hannes Mühleisen, Thaer Samar, Jimmy Lin, and Arjen de Vries. 2014 · 2014
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A deep relevance matching model for ad-hoc retrieval
Jiafeng Guo, Yixing Fan, Qingyao Ai, and W. Bruce Croft. 2016 · 2016
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Toward reproducible baselines: The open-source IR reproducibility challenge
Jimmy Lin, Matt Crane, Andrew Trotman, Jamie Callan, Ishan Chattopadhyaya, John Foley, Grant Ingersoll, Craig Macdonald, and Sebastiano Vigna. 2016 · 2016
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Co-PACRR: A context-aware neural IR model for ad-hoc retrieval
Kai Hui, Andrew Yates, Klaus Berberich, and Gerard de Melo. 2018 · 2018
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TREMA-UNH at TREC 2018: Complex answer retrieval and news track
Sumanta Kashyapi, Shubham Chatterjee, Jordan Ramsdell, and Laura Dietz. 2018 · 2018
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Query driven algorithm selection in early stage retrieval
Joel Mackenzie, Shane Culpepper, Roi Blanco, Matt Crane, Charles Clarke, and Jimmy Lin. 2018 · 2018
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Neural information retrieval: At the end of the early years
Kezban Dilek Onal, Ye Zhang, Ismail Sengor Altingovde, Md Mustafizur Rahman, Pinar Karagoz, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner, Vivek Khetan, Tyler McDonnell, An Thanh Nguyen, Dan Xu, Byron C. Wallace, Maarten de Rijke, and Matthew Lease. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
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Efficient cost-aware cascade ranking in multi-stage retrieval
Ruey-Cheng Chen, Luke Gallagher, Roi Blanco, and J. Shane Culpepper. 2017 · 2017
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TREC complex answer retrieval overview
Laura Dietz, Manisha Verma, Filip Radlinski, and Nick Craswell. 2017 · 2017
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Efficient natural language response suggestion for Smart Reply
Matthew Henderson, Rami Al-Rfou, Brian Strope, Yun hsuan Sung, Laszlo Lukacs, Ruiqi Guo, Sanjiv Kumar, Balint Miklos, and Ray Kurzweil. 2017 · 2017
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Cascade ranking for operational e-commerce search
Shichen Liu, Fei Xiao, Wenwu Ou, and Luo Si. 2017 · 2017
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Contextualized PACRR for complex answer retrieval
Sean MacAvaney, Andrew Yates, and Kai Hui. 2017 · 2017
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Learning to match using local and distributed representations of text for web search
Bhaskar Mitra, Fernando Diaz, and Nick Craswell. 2017 · 2017
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Semi-supervised sequence tagging with bidirectional language models
Matthew E. Peters, Waleed Ammar, Chandra Bhagavatula, and Russell Power. 2017 · 2017
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Anserini: Reproducible ranking baselines using Lucene
Peilin Yang, Hui Fang, and Jimmy Lin. 2018 · 2018
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From neural re-ranking to neural ranking: Learning a sparse representation for inverted indexing
Hamed Zamani, Mostafa Dehghani, W. Bruce Croft, Erik Learned-Miller, and Jaap Kamps. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Efficient interaction-based neural ranking with locality sensitive hashing
Shiyu Ji, Jinjin Shao, and Tao Yang. 2019 · 2019
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The neural hype and comparisons against weak baselines
Jimmy Lin. 2019 · 2019
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CEDR: Contextualized embeddings for document ranking
Sean MacAvaney, Andrew Yates, Arman Cohan, and Nazli Goharian. 2019 · 2019
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An introduction to neural information retrieval
Bhaskar Mitra and Nick Craswell. 2019 · 2019
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Critically examining the “neural hype”: weak baselines and the additivity of effectiveness gains from neural ranking models
Wei Yang, Kuang Lu, Peilin Yang, and Jimmy Lin. 2019a · 2019
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End-to-end open-domain question answering with BERTserini
Wei Yang, Yuqing Xie, Aileen Lin, Xingyu Li, Luchen Tan, Kun Xiong, Ming Li, and Jimmy Lin. 2019b · 2019
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Cross-domain modeling of sentence-level evidence for document retrieval
Zeynep Akkalyoncu Yilmaz, Wei Yang, Haotian Zhang, and Jimmy Lin. 2019 · 2019
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