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Much recent research on information retrieval has focused on how to transfer from one task (typically with abundant supervised data) to various other tasks where supervision is limited, with the implicit assumption that it is possible to generalize from one task to all the rest.
Rodrigo Nogueira and Kyunghyun Cho · 1901
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Efficient inner product approximation in hybrid spaces
Xiang Wu, Ruiqi Guo, David Simcha, Dave Dopson, and Sanjiv Kumar · 1903
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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 · 2010
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Learning discriminative projections for text similarity measures
Wen-tau Yih, Kristina Toutanova, John C. Platt, and Christopher Meek · 2011
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A deep relevance matching model for ad-hoc retrieval
Jiafeng Guo, Yixing Fan, Qingyao Ai, and W. Bruce Croft · 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
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Deep sentence embedding using long short-term memory networks: Analysis and application to information retrieval
Hamid Palangi, Li Deng, Yelong Shen, Jianfeng Gao, Xiaodong He, Jianshu Chen, Xinying Song, and Rabab Ward · 2016
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Dbpedia-entity v2: A test collection for entity search
Faegheh Hasibi, Fedor Nikolaev, Chenyan Xiong, Krisztian Balog, Svein Erik Bratsberg, Alexander Kotov, and Jamie Callan · 2017
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PACRR: A position-aware neural IR model for relevance matching
Kai Hui, Andrew Yates, Klaus Berberich, and Gerard de Melo · 2017
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End-to-end neural ad-hoc ranking with kernel pooling
Chenyan Xiong, Zhuyun Dai, Jamie Callan, Zhiyuan Liu, and Russell Power · 2017
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Convolutional neural networks for soft-matching n-grams in ad-hoc search
Zhuyun Dai, Chenyan Xiong, Jamie Callan, and Zhiyuan Liu · 2018
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End-to-end retrieval in continuous space
Daniel Gillick, Alessandro Presta, and Gaurav Singh Tomar · 2018
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Www’18 open challenge: financial opinion mining and question answering
Macedo Maia, Siegfried Handschuh, André Freitas, Brian Davis, Ross McDermott, Manel Zarrouk, and Alexandra Balahur · 2018
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Deep relevance ranking using enhanced document-query interactions
Ryan McDonald, George Brokos, and Ion Androutsopoulos · 2018
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FEVER: a large-scale dataset for fact extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal · 2018
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HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning · 2018
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Synthetic QA corpora generation with roundtrip consistency
Chris Alberti, Daniel Andor, Emily Pitler, Jacob Devlin, and Michael Collins · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou · 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, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov · 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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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Cited alongside, same era.
Pre-training tasks for embedding-based large-scale retrieval
Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, and Sanjiv Kumar · 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
Cited alongside, same era.
ColBERT: Efficient and effective passage search via contextualized late interaction over BERT
Omar Khattab and Matei Zaharia · 2020
Cited alongside, same era.
Document ranking with a pretrained sequence-to-sequence model
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin · 2020
Cited alongside, same era.
PAIR: Leveraging passage-centric similarity relation for improving dense passage retrieval
Ruiyang Ren, Shangwen Lv, Yingqi Qu, Jing Liu, Wayne Xin Zhao, QiaoQiao She, Hua Wu, Haifeng Wang, and Ji-Rong Wen · 2021
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RocketQAv2: A joint training method for dense passage retrieval and passage re-ranking
Ruiyang Ren, Yingqi Qu, Jing Liu, Wayne Xin Zhao, QiaoQiao She, Hua Wu, Haifeng Wang, and Ji-Rong Wen · 2021
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Multitask prompted training enables zero-shot task generalization
Victor Sanh, Albert Webson, Colin Raffel, Stephen H Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, et al · 2021
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Exploiting cloze-questions for few-shot text classification and natural language inference
Timo Schick and Hinrich Schütze · 2021
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It’s not just size that matters: Small language models are also few-shot learners
Timo Schick and Hinrich Schütze · 2021
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam M. Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, W. Li, and Peter J. Liu · 2020
Cited alongside, same era.
End-to-end synthetic data generation for domain adaptation of question answering systems
Siamak Shakeri, Cicero Nogueira dos Santos, Henghui Zhu, Patrick Ng, Feng Nan, Zhiguo Wang, Ramesh Nallapati, and Bing Xiang · 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
Cited alongside, same era.
SPLADE v2: Sparse lexical and expansion model for information retrieval
Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant · 2021
Cited alongside, same era.
Condenser: a pre-training architecture for dense retrieval
Luyu Gao and Jamie Callan · 2021
Cited alongside, same era.
COIL: Revisit exact lexical match in information retrieval with contextualized inverted list
Luyu Gao, Zhuyun Dai, and Jamie Callan · 2021
Cited alongside, same era.
Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen · 2021
Cited alongside, same era.
Later among the works it cites.
Few-shot text generation with natural language instructions
Timo Schick and Hinrich Schütze · 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
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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
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Inpars: Unsupervised dataset generation for information retrieval
Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, and Rodrigo Nogueira · 2022
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Unsupervised corpus aware language model pre-training for dense passage retrieval
Luyu Gao and Jamie Callan · 2022
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Cutting down on prompts and parameters: Simple few-shot learning with language models
Robert Logan IV, Ivana Balazevic, Eric Wallace, Fabio Petroni, Sameer Singh, and Sebastian Riedel · 2022
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Text and code embeddings by contrastive pre-training
Arvind Neelakantan, Tao Xu, Raul Puri, Alec Radford, Jesse Michael Han, Jerry Tworek, Qiming Yuan, Nikolas A. Tezak, Jong Wook Kim, Chris Hallacy, Johannes Heidecke, Pranav Shyam, Boris Power, Tyna Eloundou Nekoul, Girish Sastry, Gretchen Krueger, David P. Schnurr, Felipe Petroski Such, Kenny Sai-Kin Hsu, Madeleine Thompson, Tabarak Khan, Toki Sherbakov, Joanne Jang, Peter Welinder, and Lilian Weng · 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
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A thorough examination on zero-shot dense retrieval, 2022
Ruiyang Ren, Yingqi Qu, Jing Liu, Wayne Xin Zhao, Qifei Wu, Yuchen Ding, Hua Wu, Haifeng Wang, and Ji-Rong Wen · 2022
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No parameter left behind: How distillation and model size affect zero-shot retrieval
Guilherme Moraes Rosa, Luiz Bonifacio, Vitor Jeronymo, Hugo Abonizio, Marzieh Fadaee, Roberto Lotufo, and Rodrigo Nogueira · 2022
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Improving passage retrieval with zero-shot question generation
Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, and Luke Zettlemoyer · 2022
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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 · 2022
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Lamda: Language models for dialog applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed H. Chi, and Quoc Le · 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
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Adversarial retriever-ranker for dense text retrieval
Hang Zhang, Yeyun Gong, Yelong Shen, Jiancheng Lv, Nan Duan, and Weizhu Chen · 2022
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