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Retriever-reader models achieve competitive performance across many different NLP tasks such as open question answering and dialogue conversations.
End-to-end open-domain question answering with bertserini
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Kilt: a benchmark for knowledge intensive language tasks
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Efficient object localization using convolutional networks
Jonathan Tompson, Ross Goroshin, Arjun Jain, Yann LeCun, and Christoph Bregler. 2015 · 2015
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Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
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Decoupled weight decay regularization
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Evidentiality-guided generation for knowledge-intensive nlp tasks
Akari Asai, Matt Gardner, and Hannaneh Hajishirzi. 2021 · 2021
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R2-d2: A modular baseline for open-domain question answering
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Contextual dropout: An efficient sample-dependent dropout module
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Riccardo Grazzi, Massimiliano Pontil, and Saverio Salzo. 2021 · 2021
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On stochastic moving-average estimators for non-convex optimization
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Escaping saddles with stochastic gradients
Hadi Daneshmand, Jonas Kohler, Aurelien Lucchi, and Thomas Hofmann. 2018 · 2018
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Wizard of wikipedia: Knowledge-powered conversational agents
Emily Dinan, Stephen Roller, Kurt Shuster, Angela Fan, Michael Auli, and Jason Weston. 2018 · 2018
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Dropblock: A regularization method for convolutional networks
Golnaz Ghiasi, Tsung-Yi Lin, and Quoc V Le. 2018 · 2018
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Hanxiao Liu, Karen Simonyan, and Yiming Yang. 2018 · 2018
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Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le. 2018 · 2018
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Momentum-based variance reduction in non-convex sgd
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Natural Questions: a benchmark for question answering research
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Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, and Tianbao Yang. 2021 · 2021
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Distilling knowledge from reader to retriever for question answering
Gautier Izacard and Edouard Grave. 2021 · 2021
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Bilevel optimization: Convergence analysis and enhanced design
Kaiyi Ji, Junjie Yang, and Yingbin Liang. 2021 · 2021
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A near-optimal algorithm for stochastic bilevel optimization via double-momentum
Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, and Zhuoran Yang. 2021 · 2021
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Relevance-guided supervision for openqa with colbert
Omar Khattab, Christopher Potts, and Matei Zaharia. 2021 · 2021
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Robustifying multi-hop qa through pseudo-evidentiality training
Kyungjae Lee, Seung-won Hwang, Sang-eun Han, and Dohyeon Lee. 2021 · 2021
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Entity-based knowledge conflicts in question answering
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Sparse, dense, and attentional representations for text retrieval
Yi Luan, Jacob Eisenstein, Kristina Toutanova, and Michael Collins. 2021 · 2021
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Multi-task retrieval for knowledge-intensive tasks
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Hindsight: Posterior-guided training of retrievers for improved open-ended generation
Ashwin Paranjape, Omar Khattab, Christopher Potts, Matei Zaharia, and Christopher D Manning. 2021 · 2021
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Faviq: Fact verification from information-seeking questions
Jungsoo Park, Sewon Min, Jaewoo Kang, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2021 · 2021
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Attention-guided generative models for extractive question answering
Peng Xu, Davis Liang, Zhiheng Huang, and Bing Xiang. 2021 · 2021
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Provably faster algorithms for bilevel optimization
Junjie Yang, Kaiyi Ji, and Yingbin Liang. 2021 · 2021
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Dropnas: Grouped operation dropout for differentiable architecture search
Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, and Yong Yu. 2022 · 2022
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