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Open-domain Question Answering models which directly leverage question-answer (QA) pairs, such as closed-book QA (CBQA) models and QA-pair retrievers, show promise in terms of speed and memory compared to conventional models which retrieve and read from text corpora.
Evaluating Rewards for Question Generation Models
Tom Hosking and Sebastian Riedel. 2019 · 1902
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Document Expansion by Query Prediction
Rodrigo Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho. 2019 · 1904
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fairseq: A Fast, Extensible Toolkit for Sequence Modeling
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli. 2019 · 1904
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Quizbowl: The Case for Incremental Question Answering
Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, and Jordan Boyd-Graber. 2019 · 1904
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Data Augmentation for BERT Fine-Tuning in Open-Domain Question Answering
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Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston. 2020 · 1905
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Roberta: A robustly optimized bert pretraining approach
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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. 2019b · 1907
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019a · 1910
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HuggingFace’s Transformers: State-of-the-art Natural Language Processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi 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 M. Rush. 2020 · 1910
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Generalizing Natural Language Analysis through Span-relation Representations
Zhengbao Jiang, Wei Xu, Jun Araki, and Graham Neubig. 2020b · 1911
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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, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 1912
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Freebase: A shared database of structured general human knowledge
Kurt D. Bollacker, Robert P. Cook, and Patrick Tufts. 2007 · 1963
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Greedy function approximation: A gradient boosting machine
Jerome H. Friedman. 2001 · 2001
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REALM: Retrieval-Augmented Language Model Pre-Training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2002
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How Much Knowledge Can You Pack Into the Parameters of a Language Model?
Adam Roberts, Colin Raffel, and Noam Shazeer. 2020 · 2002
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Entities as Experts: Sparse Memory Access with Entity Supervision
Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, Eunsol Choi, and Tom Kwiatkowski. 2020 · 2004
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Dense Passage Retrieval for Open-Domain Question Answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020b · 2004
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AmbigQA: Answering Ambiguous Open-domain Questions
Sewon Min, Julian Michael, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2020b · 2004
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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Patrick Lewis, Ethan Perez, Aleksandara Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020a · 2005
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OntoNotes: the 90% solution
Eduard Hovy, Mitchell Marcus, Martha Palmer, Lance Ramshaw, and Ralph Weischedel. 2006 · 2006
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Open-Domain Question Answering with Pre-Constructed Question Spaces
Jinfeng Xiao, Lidan Wang, Franck Dernoncourt, Trung Bui, Tong Sun, and Jiawei Han. 2020 · 2006
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Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
Gautier Izacard and Edouard Grave. 2020 · 2007
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Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge
Pat Verga, Haitian Sun, Livio Baldini Soares, and William W. Cohen. 2020 · 2007
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Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasets
Reading Wikipedia to Answer Open-Domain Questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
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Learning to Ask: Neural Question Generation for Reading Comprehension
Xinya Du, Junru Shao, and Claire Cardie. 2017 · 2017
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spaCy 2: Natural language understanding with Bloom embeddings, convolutional neural networks and incremental parsing
Matthew Honnibal and Ines Montani. 2017 · 2017
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Billion-scale similarity search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2017 · 2017
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TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
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Patrick Lewis, Pontus Stenetorp, and Sebastian Riedel. 2020b · 2008
Cited alongside, same era.
Accelerating Real-Time Question Answering via Question Generation
Yuwei Fang, Shuohang Wang, Zhe Gan, Siqi Sun, and Jingjing Liu. 2020 · 2009
Cited alongside, same era.
KILT: a Benchmark for Knowledge Intensive Language Tasks
Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vassilis Plachouras, Tim Rocktäschel, and Sebastian Riedel. 2020b · 2009
Cited alongside, same era.
Challenges in Information Seeking QA:Unanswerable Questions and Paragraph Retrieval
Akari Asai and Eunsol Choi. 2020 · 2010
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Autoregressive Entity Retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel, and Fabio Petroni. 2020 · 2010
Cited alongside, same era.
Every Model Learned by Gradient Descent Is Approximately a Kernel Machine
Pedro Domingos. 2020 · 2012
Cited alongside, same era.
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
Cited alongside, same era.
How Can We Know When Language Models Know?
Zhengbao Jiang, Jun Araki, Haibo Ding, and Graham Neubig. 2020a · 2012
Cited alongside, same era.
Nicholas FitzGerald, Julian Michael, Luheng He, and Luke Zettlemoyer. 2018 · 2018
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Generative Question Answering: Learning to Answer the Whole Question
Mike Lewis and Angela Fan. 2018 · 2018
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Yu A. Malkov and D. A. Yashunin. 2018 · 2018
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Know What You Don’t Know: Unanswerable Questions for SQuAD
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
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Phrase-Indexed Question Answering: A New Challenge for Scalable Document Comprehension
Minjoon Seo, Tom Kwiatkowski, Ankur Parikh, Ali Farhadi, and Hannaneh Hajishirzi. 2018 · 2018
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Safer Classification by Synthesis
William Wang, Angelina Wang, Aviv Tamar, Xi Chen, and Pieter Abbeel. 2018 · 2018
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Synthetic QA Corpora Generation with Roundtrip Consistency
Chris Alberti, Daniel Andor, Emily Pitler, Jacob Devlin, and Michael Collins. 2019 · 2019
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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A discrete hard EM approach for weakly supervised question answering
Sewon Min, Danqi Chen, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2019 · 2019
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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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Open-domain question answering
Danqi Chen and Wen-tau Yih. 2020 · 2020
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Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
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NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
Sewon Min, Jordan Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, and Wen-tau Yih. 2020a · 2020
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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. 2020 · 2020
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