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Product quantization (PQ) is a widely used technique for ad-hoc retrieval.
Beyond product quantization: Deep progressive quantization for image retrieval
Lianli Gao, Xiaosu Zhu, Jingkuan Song, Zhou Zhao, and Heng Tao Shen. 2019 · 1906
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Kepler: A unified model for knowledge embedding and pre-trained language representation
Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu, Zhiyuan Liu, Juanzi Li, and Jian Tang. 2019 · 1911
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Sparse, dense, and attentional representations for text retrieval
Yi Luan, Jacob Eisenstein, Kristina Toutanova, and Michael Collins. 2020 · 2005
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Product quantization for nearest neighbor search
Herve Jegou, Matthijs Douze, and Cordelia Schmid. 2010 · 2010
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Yingqi Qu, Yuchen Ding, Jing Liu, Kai Liu, Ruiyang Ren, Xin Zhao, Daxiang Dong, Hua Wu, and Haifeng Wang. 2020 · 2010
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Searching in one billion vectors: re-rank with source coding
Hervé Jégou, Romain Tavenard, Matthijs Douze, and Laurent Amsaleg. 2011 · 2011
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Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville. 2013 · 2013
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Optimized product quantization
Tiezheng Ge, Kaiming He, Qifa Ke, and Jian Sun. 2013 · 2013
Cited alongside, same era.
Deep quantization network for efficient image retrieval
Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu, and Qingfu Wen. 2016 · 2016
Cited alongside, same era.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al. 2016 · 2016
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Deep visual-semantic quantization for efficient image retrieval
Yue Cao, Mingsheng Long, Jianmin Wang, and Shichen Liu. 2017 · 2017
Cited alongside, same era.
Learning dense representations for entity retrieval
Daniel Gillick, Sayali Kulkarni, Larry Lansing, Alessandro Presta, Jason Baldridge, Eugene Ie, and Diego Garcia-Olano. 2019 · 2019
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End-to-end supervised product quantization for image search and retrieval
Benjamin Klein and Lior Wolf. 2019 · 2019
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Differentiable product quantization for end-to-end embedding compression
Ting Chen, Lala Li, and Yizhou Sun. 2020 · 2020
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Embedding-based retrieval in facebook search
Jui-Ting Huang, Ashish Sharma, Shuying Sun, Li Xia, David Zhang, Philip Pronin, Janani Padmanabhan, Giuseppe Ottaviano, and Linjun Yang. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Scalable zero-shot entity linking with dense entity retrieval
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
MIND: A large-scale dataset for news recommendation
Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, Chuhan Wu, Tao Qi, Jianxun Lian, Danyang Liu, Xing Xie, Jianfeng Gao, Winnie Wu, and Ming Zhou. 2020a
Cited in the paper.
Ledell Wu, Fabio Petroni, Martin Josifoski, Sebastian Riedel, and Luke Zettlemoyer. 2020b · 2020
Later among the works it cites.