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Passage retrieval aims to retrieve relevant passages from large collections of the open-domain corpus.
Document expansion by query prediction
Rodrigo Frassetto Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho. 2019 · 1904
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The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al. 2009 · 2009
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MS MARCO: A human generated machine reading comprehension dataset
Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 2016 · 2016
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Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M. Voorhees. 2020 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
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Billion-scale similarity search with GPUs
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Overview of the trec 2020 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2021 · 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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SPLADE: sparse lexical and expansion model for first stage ranking
Thibault Formal, Benjamin Piwowarski, and Stéphane Clinchant. 2021b · 2021
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Less is more: Pretrain a strong Siamese encoder for dense text retrieval using a weak decoder
Shuqi Lu, Di He, Chenyan Xiong, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, and Arnold Overwijk. 2021 · 2021
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RocketQA: An optimized training approach to dense passage retrieval for open-domain question answering
Yingqi Qu, Yuchen Ding, Jing Liu, Kai Liu, Ruiyang Ren, Wayne Xin Zhao, Daxiang Dong, Hua Wu, and Haifeng Wang. 2021 · 2021
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BEIR: A heterogenous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021
Unsupervised corpus aware language model pre-training for dense passage retrieval
Luyu Gao and Jamie Callan. 2022 · 2022
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Lexmae: Lexicon-bottlenecked pretraining for large-scale retrieval
Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Xiaolong Huang, Binxing Jiao, Linjun Yang, and Daxin Jiang. 2022 · 2022
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RetroMAE: Pre-training retrieval-oriented language models via masked auto-encoder
Shitao Xiao, Zheng Liu, Yingxia Shao, and Zhao Cao. 2022 · 2022
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LED: lexicon-enlightened dense retriever for large-scale retrieval
Kai Zhang, Chongyang Tao, Tao Shen, Can Xu, Xiubo Geng, Binxing Jiao, and Daxin Jiang. 2022 · 2022
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Master: Multi-task pre-trained bottlenecked masked autoencoders are better dense retrievers
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Exploring dual encoder architectures for question answering
Zhe Dong, Jianmo Ni, Dan Bikel, Enrique Alfonseca, Yuan Wang, Chen Qu, and Imed Zitouni. 2022 · 2022
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SPLADE v2: Sparse lexical and expansion model for information retrieval
Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. 2021a
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Simlm: Pre-training with representation bottleneck for dense passage retrieval
Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, and Furu Wei. 2022a
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Image as a foreign language: Beit pretraining for all vision and vision-language tasks
Wenhui Wang, Hangbo Bao, Li Dong, Johan Bjorck, Zhiliang Peng, Qiang Liu, Kriti Aggarwal, Owais Khan Mohammed, Saksham Singhal, Subhojit Som, and Furu Wei. 2022b
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Query-as-context pre-training for dense passage retrieval
Xing Wu, Guangyuan Ma, and Songlin Hu. 2022a
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Contextual masked auto-encoder for dense passage retrieval
Xing Wu, Guangyuan Ma, Meng Lin, Zijia Lin, Zhongyuan Wang, and Songlin Hu. 2022b
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Kun Zhou, Xiao Liu, Yeyun Gong, Wayne Xin Zhao, Daxin Jiang, Nan Duan, and Ji-Rong Wen. 2022 · 2022
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Cot-mae v2: Contextual masked auto-encoder with multi-view modeling for passage retrieval
Xing Wu, Guangyuan Ma, Peng Wang, Meng Lin, Zijia Lin, Fuzheng Zhang, and Songlin Hu. 2023 · 2023
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