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Document retrieval has been extensively studied within the index-retrieve framework for decades, which has withstood the test of time.
Document Expansion by Query Prediction
Nogueira, R.; Yang, W.; Lin, J.; and Cho, K. 2019 · 1904
Earlier work this paper cites.
Context-Aware Document Term Weighting for Ad-Hoc Search
Dai, Z.; and Callan, J. 2020 · 1907
Earlier work this paper cites.
Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval
Dai, Z.; and Callan, J. 2019 · 1910
Earlier work this paper cites.
Passage-Level Evidence in Document Retrieval
Callan, J. P. 1994 · 1994
Earlier work this paper cites.
REALM: Retrieval-Augmented Language Model Pre-Training
Guu, K.; Lee, K.; Tung, Z.; Pasupat, P.; and Chang, M. 2020 · 2002
Earlier work this paper cites.
RepBERT: Contextualized Text Embeddings for First-Stage Retrieval
Zhan, J.; Mao, J.; Liu, Y.; Zhang, M.; and Ma, S. 2020 · 2006
Earlier work this paper cites.
The Probabilistic Relevance Framework: BM25 and Beyond
Robertson, S. E.; and Zaragoza, H. 2009 · 2009
Earlier work this paper cites.
Graph-based term weighting for information retrieval
Blanco, R.; and Lioma, C. 2012 · 2012
Earlier work this paper cites.
Efficient Estimation of Word Representations in Vector Space
Mikolov, T.; Chen, K.; Corrado, G.; and Dean, J. 2013 · 2013
Earlier work this paper cites.
Graph-of-word and TW-IDF: new approach to ad hoc IR
Rousseau, F.; and Vazirgiannis, M. 2013 · 2013
Earlier work this paper cites.
Optimized Product Quantization
Ge, T.; He, K.; Ke, Q.; and Sun, J. 2014 · 2014
Earlier work this paper cites.
Glove: Global Vectors for Word Representation
Pennington, J.; Socher, R.; and Manning, C. D. 2014 · 2014
Earlier work this paper cites.
Learning to Reweight Terms with Distributed Representations
Zheng, G.; and Callan, J. 2015 · 2015
Earlier work this paper cites.
A Deep Relevance Matching Model for Ad-hoc Retrieval
Guo, J.; Fan, Y.; Ai, Q.; and Croft, W. B. 2016 · 2016
Cited alongside, same era.
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
Nguyen, T.; Rosenberg, M.; Song, X.; Gao, J.; Tiwary, S.; Majumder, R.; and Deng, L. 2016 · 2016
Cited alongside, same era.
Neural Ranking Models with Weak Supervision
Dehghani, M.; Zamani, H.; Severyn, A.; Kamps, J.; and Croft, W. B. 2017 · 2017
Cited alongside, same era.
Attention is All you Need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, L.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
An Introduction to Neural Information Retrieval
Mitra, B.; and Craswell, N. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.; Lee, K.; and Toutanova, K. 2019 · 2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 2020
Later among the works it cites.
Autoregressive Entity Retrieval
Cao, N. D.; Izacard, G.; Riedel, S.; and Petroni, F. 2021 · 2021
Later among the works it cites.
Complement Lexical Retrieval Model with Semantic Residual Embeddings
Gao, L.; Dai, Z.; Chen, T.; Fan, Z.; Durme, B. V.; and Callan, J. 2021 · 2021
Later among the works it cites.
Sparse, Dense, and Attentional Representations for Text Retrieval
Luan, Y.; Eisenstein, J.; Toutanova, K.; and Collins, M. 2021 · 2021
Later among the works it cites.
Rethinking search: making domain experts out of dilettantes
Metzler, D.; Tay, Y.; Bahri, D.; and Najork, M. 2021 · 2021
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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
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Cited alongside, same era.
Natural Questions: a Benchmark for Question Answering Research
Kwiatkowski, T.; Palomaki, J.; Redfield, O.; Collins, M.; Parikh, A. P.; Alberti, C.; Epstein, D.; Polosukhin, I.; Devlin, J.; Lee, K.; Toutanova, K.; Jones, L.; Kelcey, M.; Chang, M.; Dai, A. M.; Uszkoreit, J.; Le, Q.; and Petrov, S. 2019 · 2019
Cited alongside, same era.
Decoupled Weight Decay Regularization
Loshchilov, I.; and Hutter, F. 2019 · 2019
Cited alongside, same era.
From doc2query to docTTTTTquery
Nogueira, R.; Lin, J.; and Epistemic, A. 2019 · 2019
Cited alongside, same era.
Language Models are Few-Shot Learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D. M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; and Amodei, D. 2020 · 2020
Cited alongside, same era.
Dense Passage Retrieval for Open-Domain Question Answering
Karpukhin, V.; Oguz, B.; Min, S.; Lewis, P. S. H.; Wu, L.; Edunov, S.; Chen, D.; and Yih, W. 2020 · 2020
Cited alongside, same era.
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
Khattab, O.; and Zaharia, M. 2020 · 2020
Cited alongside, same era.
Xiong, L.; Xiong, C.; Li, Y.; Tang, K.; Liu, J.; Bennett, P. N.; Ahmed, J.; and Overwijk, A. 2021 · 2021
Later among the works it cites.
Optimizing Dense Retrieval Model Training with Hard Negatives
Zhan, J.; Mao, J.; Liu, Y.; Guo, J.; Zhang, M.; and Ma, S. 2021b · 2021
Later among the works it cites.
Autoregressive Search Engines: Generating Substrings as Document Identifiers
Bevilacqua, M.; Ottaviano, G.; Lewis, P.; Yih, W.; Riedel, S.; and Petroni, F. 2022 · 2022
Closest in time.
GERE: Generative Evidence Retrieval for Fact Verification
Chen, J.; Zhang, R.; Guo, J.; Fan, Y.; and Cheng, X. 2022 · 2022
Closest in time.
Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models
Ni, J.; Ábrego, G. H.; Constant, N.; Ma, J.; Hall, K. B.; Cer, D.; and Yang, Y. 2022 · 2022
Closest in time.
Transformer Memory as a Differentiable Search Index
Tay, Y.; Tran, V. Q.; Dehghani, M.; Ni, J.; Bahri, D.; Mehta, H.; Qin, Z.; Hui, K.; Zhao, Z.; Gupta, J. P.; Schuster, T.; Cohen, W. W.; and Metzler, D. 2022 · 2022
Closest in time.
DynamicRetriever: A Pre-training Model-based IR System with Neither Sparse nor Dense Index
Zhou, Y.; Yao, J.; Dou, Z.; Wu, L.; and Wen, J. 2022 · 2022
Closest in time.