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Given a query and a document corpus, the information retrieval (IR) task is to output a ranked list of relevant documents.
Rodrigo Frassetto Nogueira and Kyunghyun Cho · 1901
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Document expansion by query prediction, 2019b
Rodrigo Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho · 1904
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Multi-stage document ranking with bert
Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin · 1910
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Term-weighting approaches in automatic text retrieval
Gerard Salton and Christopher Buckley · 1988
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Finding what people want: Experiences with the webcrawler
Brian Pinkerton · 1994
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Information retrieval on the web
Mei Kobayashi and Koichi Takeda · 2000
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An analysis of the AskMSR question-answering system
Eric Brill, Susan Dumais, and Michele Banko · 2002
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Cumulated gain-based evaluation of IR techniques
Kalervo Järvelin and Jaana Kekäläinen · 2002
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Query length in interactive information retrieval
N. J. Belkin, D. Kelly, G. Kim, J.-Y. Kim, H.-J. Lee, G. Muresan, M.-C. Tang, X.-J. Yuan, and C. Cool · 2003
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Overview of the TREC 2019 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M. Voorhees · 2003
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Overview of the TREC 2019 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M. Voorhees · 2003
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Umass at trec 2004: Novelty and hard
Nasreen Abdul-Jaleel, James Allan, W Bruce Croft, Fernando Diaz, Leah Larkey, Xiaoyan Li, Mark D Smucker, and Courtney Wade · 2004
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Colbert: Efficient and effective passage search via contextualized late interaction over bert, 2020
Omar Khattab and Matei Zaharia · 2004
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Interactive information retrieval
Ian Ruthven · 2008
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The probabilistic relevance framework: BM25 and Beyond
Stephen Robertson and Hugo Zaragoza · 2009
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A survey of collaborative filtering techniques
Xiaoyuan Su and Taghi M. Khoshgoftaar · 2009
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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
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Deep neural networks for youtube recommendations
Paul Covington, Jay Adams, and Emre Sargin · 2016
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Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes · 2017
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From doc2query to doctttttquery
David R. Cheriton · 2019
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Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova · 2019
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End-to-end open-domain question answering with BERTserini
Wei Yang, Yuqing Xie, Aileen Lin, Xingyu Li, Luchen Tan, Kun Xiong, Ming Li, and Jimmy Lin · 2019
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Retrieval augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang · 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
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela · 2020
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Document ranking with a pretrained sequence-to-sequence model
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin · 2020
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How much knowledge can you pack into the parameters of a language model?
Adam Roberts, Colin Raffel, and Noam Shazeer · 2020
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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
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Precise zero-shot dense retrieval without relevance labels, 2022
Luyu Gao, Xueguang Ma, Jimmy Lin, and Jamie Callan · 2022
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Few-shot learning with retrieval augmented language models
Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave · 2022
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Improving passage retrieval with zero-shot question generation
Devendra Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, and Luke Zettlemoyer · 2022
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QUILL: Query intent with large language models using retrieval augmentation and multi-stage distillation
Krishna Srinivasan, Karthik Raman, Anupam Samanta, Lingrui Liao, Luca Bertelli, and Michael Bendersky · 2022
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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 · 2020
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mmarco: A multilingual version of MS MARCO passage ranking dataset
Luiz Henrique Bonifacio, Israel Campiotti, Roberto de Alencar Lotufo, and Rodrigo Frassetto Nogueira · 2021
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DeepXML: A deep extreme multi-label learning framework applied to short text documents
Kunal Dahiya, Deepak Saini, Anshul Mittal, Ankush Shaw, Kushal Dave, Akshay Soni, Himanshu Jain, Sumeet Agarwal, and Manik Varma · 2021
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Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, and Allan Hanbury · 2021
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Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, and Rodrigo Nogueira · 2021
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Retrieval augmented code generation and summarization
Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang · 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
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Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Guodong Long, Binxing Jiao, and Daxin Jiang · 2022
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OpenAI · 2023
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