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Neural retrievers based on pre-trained language models (PLMs), such as dual-encoders, have achieved promising performance on the task of open-domain question answering (QA).
Rodrigo Nogueira and Kyunghyun Cho. 2019 · 1901
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Document expansion by query prediction
Rodrigo Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho. 2019c · 1904
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Ernie: Enhanced representation through knowledge integration
Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Xuyi Chen, Han Zhang, Xin Tian, Danxiang Zhu, Hao Tian, and Hua Wu. 2019 · 1904
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Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston. 2019 · 1905
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Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 1906
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 1908
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Tinybert: Distilling bert for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2019 · 1909
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Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019 · 1909
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Multi-stage document ranking with bert
Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin. 2019b · 1910
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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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Pre-training tasks for embedding-based large-scale retrieval
Wei-Cheng Chang, Felix X Yu, Yin-Wen Chang, Yiming Yang, and Sanjiv Kumar. 2020 · 2002
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2004
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Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2020 · 2006
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk. 2020 · 2007
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Generation-augmented retrieval for open-domain question answering
Yuning Mao, Pengcheng He, Xiaodong Liu, Yelong Shen, Jianfeng Gao, Jiawei Han, and Weizhu Chen. 2020 · 2009
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Neural retrieval for question answering with cross-attention supervised data augmentation
Yinfei Yang, Ning Jin, Kuo Lin, Mandy Guo, and Daniel Cer. 2020 · 2009
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Improving efficient neural ranking models with cross-architecture knowledge distillation
Sebastian Hofstätter, Sophia Althammer, Michael Schröder, Mete Sertkan, and Allan Hanbury. 2020 · 2010
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Distilling dense representations for ranking using tightly-coupled teachers
Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. 2020 · 2010
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Yingqi Qu, Yuchen Ding, Jing Liu, Kai Liu, Ruiyang Ren, Wayne Xin Zhao, Daxiang Dong, Hua Wu, and Haifeng Wang. 2020 · 2010
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Is retriever merely an approximator of reader?
Sohee Yang and Minjoon Seo. 2020 · 2010
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Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers
Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, and Ming Zhou. 2020 · 2020
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Improving bi-encoder document ranking models with two rankers and multi-teacher distillation
Jaekeol Choi, Euna Jung, Jangwon Suh, and Wonjong Rhee. 2021 · 2021
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Unsupervised corpus aware language model pre-training for dense passage retrieval
Luyu Gao and Jamie Callan. 2021 · 2021
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Semantic models for the first-stage retrieval: A comprehensive review
Jiafeng Guo, Yinqiong Cai, Yixing Fan, Fei Sun, Ruqing Zhang, and Xueqi Cheng. 2021 · 2021
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Efficiently teaching an effective dense retriever with balanced topic aware sampling
Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, and Allan Hanbury. 2021 · 2021
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Nils Reimers and Iryna Gurevych. 2020 · 2012
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean, et al. 2015 · 2015
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Training deep nets with sublinear memory cost
Tianqi Chen, Bing Xu, Chiyuan Zhang, and Carlos Guestrin. 2016 · 2016
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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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Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory Diamos, Erich Elsen, David Garcia, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, et al. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Anserini: Enabling the use of lucene for information retrieval research
Peilin Yang, Hui Fang, and Jimmy Lin. 2017 · 2017
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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
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In-batch negatives for knowledge distillation with tightly-coupled teachers for dense retrieval
Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. 2021 · 2021
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Pre-trained language model for web-scale retrieval in baidu search
Yiding Liu, Weixue Lu, Suqi Cheng, Daiting Shi, Shuaiqiang Wang, Zhicong Cheng, and Dawei Yin. 2021 · 2021
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Sparse, dense, and attentional representations for text retrieval
Yi Luan, Jacob Eisenstein, Kristina Toutanova, and Michael Collins. 2021 · 2021
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Large dual encoders are generalizable retrievers
Jianmo Ni, Chen Qu, Jing Lu, Zhuyun Dai, Gustavo Hernández Ábrego, Ji Ma, Vincent Y Zhao, Yi Luan, Keith B Hall, Ming-Wei Chang, et al. 2021 · 2021
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Colbertv2: Effective and efficient retrieval via lightweight late interaction
Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, and Matei Zaharia. 2021 · 2021
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Ernie 3.0: Large-scale knowledge enhanced pre-training for language understanding and generation
Yu Sun, Shuohuan Wang, Shikun Feng, Siyu Ding, Chao Pang, Junyuan Shang, Jiaxiang Liu, Xuyi Chen, Yanbin Zhao, Yuxiang Lu, et al. 2021 · 2021
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Gpl: Generative pseudo labeling for unsupervised domain adaptation of dense retrieval
Kexin Wang, Nandan Thakur, Nils Reimers, and Iryna Gurevych. 2021 · 2021
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R-drop: regularized dropout for neural networks
Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu, et al. 2021 · 2021
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Speeding up deep model training by sharing weights and then unsharing
Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, and Denny Zhou. 2021 · 2021
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Adversarial retriever-ranker for dense text retrieval
Hang Zhang, Yeyun Gong, Yelong Shen, Jiancheng Lv, Nan Duan, and Weizhu Chen. 2021 · 2021
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Fast semantic matching via flexible contextualized interaction
Wenwen Ye, Yiding Liu, Lixin Zou, Hengyi Cai, Suqi Cheng, Shuaiqiang Wang, and Dawei Yin. 2022 · 2022
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