Fetching the paper…
Reading the bibliography…
We present a new zero-shot dense retrieval (ZeroDR) method, COCO-DR, to improve the generalization ability of dense retrieval by combating the distribution shifts between source training tasks and target scenarios.
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, et al. 2020 · 1901
Earlier work this paper cites.
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
Earlier work this paper cites.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
Earlier work this paper cites.
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 · 1942
Earlier work this paper cites.
Least squares quantization in pcm
Stuart Lloyd. 1982 · 1982
Earlier work this paper cites.
Indexing by latent semantic analysis
Scott Deerwester, Susan T Dumais, George W Furnas, Thomas K Landauer, and Richard Harshman. 1990 · 1990
Earlier work this paper cites.
Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
Earlier work this paper cites.
Overview of the trec 2004 robust retrieval track
Ellen M Voorhees et al. 2004 · 2004
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al. 2009 · 2009
Earlier work this paper cites.
Improved consistent sampling, weighted minhash and l1 sketching
Sergey Ioffe. 2010 · 2010
Earlier work this paper cites.
CLIMATE-FEVER: A dataset for verification of real-world climate claims
Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, Massimiliano Ciaramita, and Markus Leippold. 2020 · 2012
Earlier work this paper cites.
Learning deep structured semantic models for web search using clickthrough data
Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry Heck. 2013 · 2013
Earlier work this paper cites.
A theoretical analysis of ndcg ranking measures
Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Wei Chen, and Tie-Yan Liu. 2013 · 2013
Earlier work this paper cites.
CQADupStack: A benchmark data set for community question-answering research
Doris Hoogeveen, Karin M. Verspoor, and Timothy Baldwin. 2015 · 2015
Earlier work this paper cites.
An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition
George Tsatsaronis, Georgios Balikas, Prodromos Malakasiotis, Ioannis Partalas, Matthias Zschunke, Michael R Alvers, Dirk Weissenborn, Anastasia Krithara, Sergios Petridis, Dimitris Polychronopoulos, et al. 2015 · 2015
Earlier work this paper cites.
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
Earlier work this paper cites.
A full-text learning to rank dataset for medical information retrieval
Vera Boteva, Demian Gholipour, Artem Sokolov, and Stefan Riezler. 2016 · 2016
Earlier work this paper cites.
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 · 2017
Earlier work this paper cites.
Trec 2018 news track overview
Ian Soboroff, Shudong Huang, and Donna Harman. 2018 · 2018
Earlier work this paper cites.
A data collection for evaluating the retrieval of related tweets to news articles
Axel Suarez, Dyaa Albakour, David Corney, Miguel Martinez, and José Esquivel. 2018 · 2018
Earlier work this paper cites.
FEVER: a large-scale dataset for fact extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018 · 2018
Earlier work this paper cites.
Retrieval of the best counterargument without prior topic knowledge
Henning Wachsmuth, Shahbaz Syed, and Benno Stein. 2018 · 2018
Earlier work this paper cites.
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 · 2018
Earlier work this paper cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
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 · 2019
Cited alongside, same era.
Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
Cited alongside, same era.
Distributionally robust language modeling
Yonatan Oren, Shiori Sagawa, Tatsunori B. Hashimoto, and Percy Liang. 2019 · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. 2019 · 2019
Cited alongside, same era.
UDALM: Unsupervised domain adaptation through language modeling
Constantinos Karouzos, Georgios Paraskevopoulos, and Alexandros Potamianos. 2021 · 2021
Later among the works it cites.
Openmatch: An open source library for neu-ir research
Zhenghao Liu, Kaitao Zhang, Chenyan Xiong, Zhiyuan Liu, and Maosong Sun. 2021 · 2021
Later among the works it cites.
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
Later among the works it cites.
Zero-shot neural passage retrieval via domain-targeted synthetic question generation
Ji Ma, Ivan Korotkov, Yinfei Yang, Keith Hall, and Ryan McDonald. 2021 · 2021
Later among the works it cites.
COCO-LM: Correcting and contrasting text sequences for language model pretraining
Yu Meng, Chenyan Xiong, Payal Bajaj, saurabh tiwary, Paul N. Bennett, Jiawei Han, and Xia Song. 2021 · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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 · 2019
Cited alongside, same era.
Overview of Touché 2020: Argument Retrieval
Alexander Bondarenko, Maik Fröbe, Meriem Beloucif, Lukas Gienapp, Yamen Ajjour, Alexander Panchenko, Chris Biemann, Benno Stein, Henning Wachsmuth, Martin Potthast, and Matthias Hagen. 2020 · 2020
Cited alongside, same era.
SPECTER: Document-level representation learning using citation-informed transformers
Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, and Daniel Weld. 2020 · 2020
Cited alongside, same era.
Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 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.
Colbert: Efficient and effective passage search via contextualized late interaction over bert
Omar Khattab and Matei Zaharia. 2020 · 2020
Cited alongside, same era.
Distributionally robust neural networks
Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, and Percy Liang. 2020 · 2020
Cited alongside, same era.
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
Later among the works it cites.
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.
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
Later among the works it cites.
TREC-COVID: Constructing a pandemic information retrieval test collection
Ellen Voorhees, Tasmeer Alam, Steven Bedrick, Dina Demner-Fushman, William R. Hersh, Kyle Lo, Kirk Roberts, Ian Soboroff, and Lucy Lu Wang. 2021 · 2021
Later among the works it cites.
TSDAE: Using transformer-based sequential denoising auto-encoderfor unsupervised sentence embedding learning
Kexin Wang, Nils Reimers, and Iryna Gurevych. 2021a · 2021
Later among the works it cites.
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
Later among the works it cites.
Examining and combating spurious features under distribution shift
Chunting Zhou, Xuezhe Ma, Paul Michel, and Graham Neubig. 2021 · 2021
Later among the works it cites.
From distillation to hard negative sampling: Making sparse neural ir models more effective
Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. 2022 · 2022
Closest in time.
Unsupervised corpus aware language model pre-training for dense passage retrieval
Luyu Gao and Jamie Callan. 2022 · 2022
Closest in time.
Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022 · 2022
Closest in time.
Pre-train a discriminative text encoder for dense retrieval via contrastive span prediction
Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, and Xueqi Cheng. 2022 · 2022
Closest in time.
Text and code embeddings by contrastive pre-training
Arvind Neelakantan, Tao Xu, Raul Puri, Alec Radford, Jesse Michael Han, Jerry Tworek, Qiming Yuan, Nikolas Tezak, Jong Wook Kim, Chris Hallacy, et al. 2022 · 2022
Closest in time.
Focus on the common good: Group distributional robustness follows
Vihari Piratla, Praneeth Netrapalli, and Sunita Sarawagi. 2022 · 2022
Closest in time.
A thorough examination on zero-shot dense retrieval
Ruiyang Ren, Yingqi Qu, Jing Liu, Wayne Xin Zhao, Qifei Wu, Yuchen Ding, Hua Wu, Haifeng Wang, and Ji-Rong Wen. 2022 · 2022
Closest in time.
GPL: Generative pseudo labeling for unsupervised domain adaptation of dense retrieval
Kexin Wang, Nandan Thakur, Nils Reimers, and Iryna Gurevych. 2022 · 2022
Closest in time.
A fine-grained analysis on distribution shift
Olivia Wiles, Sven Gowal, Florian Stimberg, Sylvestre-Alvise Rebuffi, Ira Ktena, Krishnamurthy Dj Dvijotham, and Ali Taylan Cemgil. 2022 · 2022
Closest in time.
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
Closest in time.
LaPraDoR: Unsupervised pretrained dense retriever for zero-shot text retrieval
Canwen Xu, Daya Guo, Nan Duan, and Julian McAuley. 2022 · 2022
Closest in time.