Fetching the paper…
Reading the bibliography…
Neural information retrieval (IR) has greatly advanced search and other knowledge-intensive language tasks.
Rodrigo Nogueira and Kyunghyun Cho. 2019 · 1901
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.
Vector quantization
Robert Gray. 1984 · 1984
Earlier work this paper cites.
Okapi at TREC-3
Stephen E Robertson, Steve Walker, Susan Jones, Micheline M Hancock-Beaulieu, Mike Gatford, et al. 1995 · 1995
Earlier work this paper cites.
Advances in Residual Vector Quantization: A Review
Christopher F Barnes, Syed A Rizvi, and Nasser M Nasrabadi. 1996 · 1996
Earlier work this paper cites.
Realm: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2002
Earlier work this paper cites.
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 · 2002
Earlier work this paper cites.
Repbert: Contextualized text embeddings for first-stage retrieval
Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, and Shaoping Ma. 2020b · 2006
Earlier work this paper cites.
DBpedia: A Nucleus for a Web of Open Data
Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 2007 · 2007
Earlier work this paper cites.
Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation
Sebastian Hofstätter, Sophia Althammer, Michael Schröder, Mete Sertkan, and Allan Hanbury. 2020 · 2010
Earlier work this paper cites.
Product quantization for nearest neighbor search
Herve Jegou, Matthijs Douze, and Cordelia Schmid. 2010 · 2010
Earlier work this paper cites.
Distilling Dense Representations for Ranking using Tightly-Coupled Teachers
Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. 2020 · 2010
Earlier work this paper cites.
Learning to retrieve: How to train a dense retrieval model effectively and efficiently
Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, and Shaoping Ma. 2020a · 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.
A memory efficient baseline for open domain question answering
Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Sebastian Riedel, and Edouard Grave. 2020 · 2012
Earlier work this paper cites.
Projected Residual Vector Quantization for ANN Search
Benchang Wei, Tao Guan, and Junqing Yu. 2014 · 2014
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.
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 · 2016
Earlier work this paper cites.
SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Earlier work this paper cites.
Optimized Residual Vector Quantization for Efficient Approximate Nearest Neighbor Search
Liefu Ai, Junqing Yu, Zebin Wu, Yunfeng He, and Tao Guan. 2017 · 2017
Earlier work this paper cites.
TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
Earlier work this paper cites.
Adacomp : Adaptive residual gradient compression for data-parallel distributed training
Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, and Kailash Gopalakrishnan. 2018 · 2018
Cited alongside, same era.
FEVER: a large-scale dataset for fact extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018 · 2018
Cited alongside, same era.
Retrieval of the best counterargument without prior topic knowledge
Henning Wachsmuth, Shahbaz Syed, and Benno Stein. 2018 · 2018
Cited alongside, same era.
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. 2018b · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Multi-vector attention models for deep re-ranking
Giulio Zhou and Jacob Devlin. 2021 · 2020
Later among the works it cites.
Improving language models by retrieving from trillions of tokens
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, et al. 2021 · 2021
Closest in time.
SDR: Efficient Neural Re-ranking using Succinct Document Representation
Nachshon Cohen, Amit Portnoy, Besnik Fetahu, and Amir Ingber. 2021 · 2021
Closest in time.
Unsupervised corpus aware language model pre-training for dense passage retrieval
Luyu Gao and Jamie Callan. 2021 · 2021
Closest in time.
COIL: Revisit exact lexical match in information retrieval with contextualized inverted list
Luyu Gao, Zhuyun Dai, and Jamie Callan. 2021 · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2019 · 2019
Cited alongside, same era.
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.
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, et al. 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.
Context-aware term weighting for first stage passage retrieval
Zhuyun Dai and Jamie Callan. 2020 · 2020
Cited alongside, same era.
Modularized transfomer-based ranking framework
Luyu Gao, Zhuyun Dai, and Jamie Callan. 2020 · 2020
Cited alongside, same era.
Closest in time.
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
Closest in time.
GooAQ: Open Question Answering with Diverse Answer Types
Daniel Khashabi, Amos Ng, Tushar Khot, Ashish Sabharwal, Hannaneh Hajishirzi, and Chris Callison-Burch. 2021 · 2021
Closest in time.
Jimmy Lin and Xueguang Ma. 2021 · 2021
Closest in time.
Sparse, Dense, and Attentional Representations for Text Retrieval
Yi Luan, Jacob Eisenstein, Kristina Toutanova, and Michael Collins. 2021 · 2021
Closest in time.
On approximate nearest neighbour selection for multi-stage dense retrieval
Craig Macdonald and Nicola Tonellotto. 2021 · 2021
Closest in time.
Learning passage impacts for inverted indexes
Antonio Mallia, Omar Khattab, Torsten Suel, and Nicola Tonellotto. 2021 · 2021
Closest in time.
Domain-matched Pre-training Tasks for Dense Retrieval
Barlas Oğuz, Kushal Lakhotia, Anchit Gupta, Patrick Lewis, Vladimir Karpukhin, Aleksandra Piktus, Xilun Chen, Sebastian Riedel, Wen-tau Yih, Sonal Gupta, et al. 2021 · 2021
Closest in time.
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
Closest in time.
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. 2021a · 2021
Closest in time.
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021
Closest in time.
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
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 N Bennett. 2021 · 2021
Closest in time.
In defense of dual-encoders for neural ranking
Aditya Krishna Menon, Sadeep Jayasumana, Seungyeon Kim, Ankit Singh Rawat, Sashank J. Reddi, and Sanjiv Kumar. 2022 · 2022
Closest in time.
Hindsight: Posterior-guided training of retrievers for improved open-ended generation
Ashwin Paranjape, Omar Khattab, Christopher Potts, Matei Zaharia, and Christopher D Manning. 2022 · 2022
Closest in time.
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
Closest in time.