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Recent developments of dense retrieval rely on quality representations of queries and contexts from pre-trained query and context encoders.
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Semantic parsing on Freebase from question-answer pairs
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Modeling of the question answering task in the yodaqa system
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Reading Wikipedia to answer open-domain questions
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Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
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NPRF: A neural pseudo relevance feedback framework for ad-hoc information retrieval
Canjia Li, Yingfei Sun, Ben He, Le Wang, Kai Hui, Andrew Yates, Le Sun, and Jungang Xu. 2018 · 2018
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From neural re-ranking to neural ranking: Learning a sparse representation for inverted indexing
Hamed Zamani, Mostafa Dehghani, W. Bruce Croft, Erik G. Learned-Miller, and Jaap Kamps. 2018 · 2018
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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 · 2019
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Latent retrieval for weakly supervised open domain question answering
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Real-time open-domain question answering with dense-sparse phrase index
Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, Ankur Parikh, Ali Farhadi, and Hannaneh Hajishirzi. 2019 · 2019
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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Question and answer test-train overlap in open-domain question answering datasets
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RocketQAv2: A joint training method for dense passage retrieval and passage re-ranking
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Simple entity-centric questions challenge dense retrievers
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
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Leveraging passage retrieval with generative models for open domain question answering
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End-to-end training of multi-document reader and retriever for open-domain question answering
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BEIR: A heterogeneous benchmark for zero-shot evaluation of information retrieval models
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Pseudo-relevance feedback for multiple representation dense retrieval
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Improving query representations for dense retrieval with pseudo relevance feedback
HongChien Yu, Chenyan Xiong, and Jamie Callan. 2021 · 2021
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Incorporating relevance feedback for information-seeking retrieval using few-shot document re-ranking
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In defense of cross-encoders for zero-shot retrieval
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