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Pre-trained language models have been successful in many knowledge-intensive NLP tasks.
RoBERTa: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Curriculum learning for dense retrieval distillation
Hansi Zeng, Hamed Zamani, and Vishwa Vinay. 2022 · 1983
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SparTerm: Learning term-based sparse representation for fast text retrieval
Yang Bai, Xiaoguang Li, Gang Wang, Chaoliang Zhang, Lifeng Shang, Jun Xu, Zhaowei Wang, Fangshan Wang, and Qun Liu. 2020 · 2010
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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, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, and Tong Wang. 2016 · 2016
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 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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Overview of the TREC 2019 deep learning track
Nick Craswell, Bhaskar Mitra, and Daniel Campos. 2019 · 2019
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Natural Questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Matthew Kelcey, Jacob Devlin, Kenton Lee, Kristina N. Toutanova, Llion Jones, Ming-Wei Chang, Andrew Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 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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Overview of the TREC 2020 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2020 · 2020
Cited alongside, same era.
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
Cited alongside, same era.
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
Cited alongside, same era.
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.
Condenser: a pre-training architecture for dense retrieval
Luyu Gao and Jamie Callan. 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
Later among the works it cites.
Simple entity-centric questions challenge dense retrievers
Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, and Danqi Chen. 2021 · 2021
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BEIR: A heterogeneous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021
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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 N. Bennett, Junaid Ahmed, and Arnold Overwijk. 2021 · 2021
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Sparsifying sparse representations for passage retrieval by top- k k masking
Jheng-Hong Yang, Xueguang Ma, and Jimmy Lin. 2021 · 2021
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Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, and Allan Hanbury. 2021 · 2021
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.
Ultra-high dimensional sparse representations with binarization for efficient text retrieval
Kyoung-Rok Jang, Junmo Kang, Giwon Hong, Sung-Hyon Myaeng, Joohee Park, Taewon Yoon, and Heecheol Seo. 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.
Jimmy Lin and Xueguang Ma. 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.
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.
Later among the works it cites.
Unsupervised corpus aware language model pre-training for dense passage retrieval
Luyu Gao and Jamie Callan. 2022 · 2022
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Tevatron: An efficient and flexible toolkit for dense retrieval
Luyu Gao, Xueguang Ma, Jimmy Lin, and Jamie Callan. 2022 · 2022
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Sebastian Hofstätter, Omar Khattab, Sophia Althammer, Mete Sertkan, and Allan Hanbury. 2022 · 2022
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A dense representation framework for lexical and semantic matching
Sheng-Chieh Lin and Jimmy Lin. 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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Learning to retrieve passages without supervision
Ori Ram, Gal Shachaf, Omer Levy, Jonathan Berant, and Amir Globerson. 2022 · 2022
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Unifier: A unified retriever for large-scale retrieval
Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Kai Zhang, and Daxin Jiang. 2022 · 2022
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Learning discrete representations via constrained clustering for effective and efficient dense retrieval
Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, and Shaoping Ma. 2022 · 2022
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Repbert: Contextualized text embeddings for first-stage retrieval
Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, and Shaoping Ma. 2020 · 2022
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