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Various techniques have been developed in recent years to improve dense retrieval (DR), such as unsupervised contrastive learning and pseudo-query generation.
Curriculum learning for dense retrieval distillation
Hansi Zeng, Hamed Zamani, and Vishwa Vinay. 2022 · 1983
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston. 2009 · 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 the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeffrey Dean. 2015 · 2015
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MS MARCO: A human generated machine reading comprehension dataset
Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, et al. 2016 · 2016
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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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Overview of the TREC 2019 deep learning track
Nick Craswell, Bhaskar Mitra, and Daniel Campos. 2019 · 2019
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Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 2019
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From doc2query to docTTTTTquery
Rodrigo Nogueira and Jimmy Lin. 2019 · 2019
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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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 · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020 · 2020
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Overview of the TREC 2020 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2020 · 2020
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Accelerating large-scale inference with anisotropic vector quantization
Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, and Sanjiv Kumar. 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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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. 2020 · 2020
Cited alongside, same era.
Salient phrase aware dense retrieval: Can a dense retriever imitate a sparse one?
Xilun Chen, Kushal Lakhotia, Barlas Oğuz, Anchit Gupta, Patrick Lewis, Stan Peshterliev, Yashar Mehdad, Sonal Gupta, and Wen tau Yih. 2021 · 2021
Cited alongside, same era.
SPLADE v2: Sparse lexical and expansion model for information retrieval
Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. 2021 · 2021
Cited alongside, same era.
Condenser: a pre-training architecture for dense retrieval
Luyu Gao and Jamie Callan. 2021 · 2021
Cited alongside, same era.
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
Task-aware retrieval with instructions
Akari Asai, Timo Schick, Patrick Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, and Wen-tau Yih. 2022 · 2022
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Promptagator: Few-shot dense retrieval from 8 examples
Zhuyun Dai, Vincent Y. Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith B. Hall, and Ming-Wei Chang. 2022 · 2022
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From distillation to hard negative sampling: Making sparse neural ir models more effective
Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. 2022 · 2022
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Unsupervised corpus aware language model pre-training for dense passage retrieval
Luyu Gao and Jamie Callan. 2022 · 2022
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Cited alongside, same era.
Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2021 · 2021
Cited alongside, same era.
Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2021 · 2021
Cited alongside, same era.
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
Cited alongside, same era.
A replication study of dense passage retriever
Xueguang Ma, Kai Sun, Ronak Pradeep, and Jimmy Lin. 2021 · 2021
Cited alongside, same era.
Wacky weights in learned sparse representations and the revenge of score-at-a-time query evaluation
Joel Mackenzie, Andrew Trotman, and Jimmy Lin. 2021 · 2021
Cited alongside, same era.
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, and Yinfei Yang. 2021 · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. 2022 · 2022
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Prod: Progressive distillation for dense retrieval
Zhenghao Lin, Yeyun Gong, Xiao Liu, Hang Zhang, Chen Lin, Anlei Dong, Jian Jiao, Jingwen Lu, Daxin Jiang, Rangan Majumder, and Nan Duan. 2022 · 2022
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Retromae: Pre-training retrieval-oriented transformers via masked auto-encoder
Zheng Liu and Yingxia Shao. 2022 · 2022
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Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Hannaneh Hajishirzi, and Daniel Khashabi. 2022 · 2022
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Domain-matched pre-training tasks for dense retrieval
Barlas Oguz, Kushal Lakhotia, Anchit Gupta, Patrick Lewis, Vladimir Karpukhin, Aleksandra Piktus, Xilun Chen, Sebastian Riedel, Scott Yih, Sonal Gupta, and Yashar Mehdad. 2022 · 2022
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Plaid: An efficient engine for late interaction retrieval
Keshav Santhanam, Omar Khattab, Christopher Potts, and Matei Zaharia. 2022 · 2022
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GPL: Generative pseudo labeling for unsupervised domain adaptation of dense retrieval
Kexin Wang, Nandan Thakur, Nils Reimers, and Iryna Gurevych. 2022 · 2022
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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. 2022 · 2022
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Zero-shot dense retrieval with momentum adversarial domain invariant representations
Ji Xin, Chenyan Xiong, Ashwin Srinivasan, Ankita Sharma, Damien Jose, and Paul Bennett. 2022 · 2022
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Coco-dr: Combating distribution shifts in zero-shot dense retrieval with contrastive and distributionally robust learning
Yue Yu, Chenyan Xiong, Si Sun, Chao Zhang, and Arnold Overwijk. 2022 · 2022
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Replug: Retrieval-augmented black-box language models
Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, and Wen-tau Yih. 2023 · 2023
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