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Relational knowledge bases (KBs) are commonly used to represent world knowledge in machines.
UNIFIEDQA: Crossing format boundaries with a single QA system
Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi. 2020 · 1907
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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. 2019 · 1907
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Zhi-Xiu Ye, Qian Chen, Wen Wang, and Zhen-Hua Ling. 2020 · 1908
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Kg-bert: Bert for knowledge graph completion
Liang Yao, Chengsheng Mao, and Yuan Luo. 2019 · 1909
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“cloze procedure”: A new tool for measuring readability
Wilson L Taylor. 1953 · 1953
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A framework for representing knowledge
Marvin Minsky. 1974 · 1974
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What is a knowledge representation?
Randall Davis, Howard Shrobe, and Peter Szolovits. 1993 · 1993
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Cyc: A large-scale investment in knowledge infrastructure
Douglas B Lenat. 1995 · 1995
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Learning cross-context entity representations from text
Jeffrey Ling, Nicholas FitzGerald, Zifei Shan, Livio Baldini Soares, Thibault Févry, David Weiss, and Tom Kwiatkowski. 2020 · 2001
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Crossing the structure chasm
Alon Y Halevy, Oren Etzioni, AnHai Doan, Zachary G Ives, Jayant Madhavan, Luke K McDowell, and Igor Tatarinov. 2003 · 2003
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Conceptnet—a practical commonsense reasoning tool-kit
Hugo Liu and Push Singh. 2004 · 2004
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Investigating pretrained language models for graph-to-text generation
Leonardo FR Ribeiro, Martin Schmitt, Hinrich Schütze, and Iryna Gurevych. 2020 · 2007
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Knowledge-aware language model pretraining
Corby Rosset, Chenyan Xiong, Minh Phan, Xia Song, Paul Bennett, and Saurabh Tiwary. 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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The tradeoffs between open and traditional relation extraction
Michele Banko and Oren Etzioni. 2008 · 2008
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Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
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Jaket: Joint pre-training of knowledge graph and language understanding
Donghan Yu, Chenguang Zhu, Yiming Yang, and Michael Zeng. 2020 · 2010
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Identifying relations for open information extraction
Anthony Fader, Stephen Soderland, and Oren Etzioni. 2011 · 2011
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Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
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Building machines that learn and think like people
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, and Samuel J Gershman. 2017 · 2017
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Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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End-to-end neural entity linking
Nikolaos Kolitsas, Octavian-Eugen Ganea, and Thomas Hofmann. 2018 · 2018
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Matching the blanks: Distributional similarity for relation learning
Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, and Tom Kwiatkowski. 2019 · 2019
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COMET: Commonsense transformers for automatic knowledge graph construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi. 2019 · 2019
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Investigating entity knowledge in BERT with simple neural end-to-end entity linking
Samuel Broscheit. 2019 · 2019
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Cracking the contextual commonsense code: Understanding commonsense reasoning aptitude of deep contextual representations
Jeff Da and Jungo Kasai. 2019 · 2019
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Commonsense knowledge mining from pretrained models
Joe Davison, Joshua Feldman, and Alexander Rush. 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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Zero-shot entity linking by reading entity descriptions
Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, and Honglak Lee. 2019 · 2019
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Knowledge enhanced contextual word representations
Matthew E. Peters, Mark Neumann, Robert Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah A. Smith. 2019 · 2019
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Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Atomic: An atlas of machine commonsense for if-then reasoning
Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A Smith, and Yejin Choi. 2019 · 2019
Cited alongside, same era.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2019 · 2019
Cited alongside, same era.
ERNIE: Enhanced language representation with informative entities
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019 · 2019
Cited alongside, same era.
Event-guided denoising for multilingual relation learning
Amith Ananthram, Emily Allaway, and Kathleen McKeown. 2020 · 2020
Cited alongside, same era.
Ernie 2.0: A continual pre-training framework for language understanding
Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Hao Tian, Hua Wu, and Haifeng Wang. 2020 · 2020
Later among the works it cites.
Pre-training is (almost) all you need: An application to commonsense reasoning
Alexandre Tamborrino, Nicola Pellicanò, Baptiste Pannier, Pascal Voitot, and Louise Naudin. 2020 · 2020
Later among the works it cites.
From natural language processing to neural databases
James Thorne, Majid Yazdani, Marzieh Saeidi, Fabrizio Silvestri, Sebastian Riedel, and Alon Halevy. 2020 · 2020
Later among the works it cites.
Scalable zero-shot entity linking with dense entity retrieval
Ledell Wu, Fabio Petroni, Martin Josifoski, Sebastian Riedel, and Luke Zettlemoyer. 2020 · 2020
Later among the works it cites.
Pretrained encyclopedia: Weakly supervised knowledge-pretrained language model
Wenhan Xiong, Jingfei Du, William Yang Wang, and Veselin Stoyanov. 2020 · 2020
Later among the works it cites.
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Entity Linking in 100 Languages
Jan A. Botha, Zifei Shan, and Daniel Gillick. 2020 · 2020
Cited alongside, same era.
Inducing relational knowledge from bert
Zied Bouraoui, Jose Camacho-Collados, and Steven Schockaert. 2020 · 2020
Cited alongside, same era.
Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 2020
Cited alongside, same era.
Contextualized end-to-end neural entity linking
Haotian Chen, Xi Li, Andrej Zukov Gregoric, and Sahil Wadhwa. 2020 · 2020
Cited alongside, same era.
Transformers as soft reasoners over language
Peter Clark, Oyvind Tafjord, and Kyle Richardson. 2020 · 2020
Cited alongside, same era.
Entities as experts: Sparse memory access with entity supervision
Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, Eunsol Choi, and Tom Kwiatkowski. 2020 · 2020
Cited alongside, same era.
A knowledge-enhanced pretraining model for commonsense story generation
Jian Guan, Fei Huang, Zhihao Zhao, Xiaoyan Zhu, and Minlie Huang. 2020 · 2020
Cited alongside, same era.
LUKE: Deep contextualized entity representations with entity-aware self-attention
Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, and Yuji Matsumoto. 2020 · 2020
Later among the works it cites.
Evaluating commonsense in pre-trained language models
Xuhui Zhou, Yue Zhang, Leyang Cui, and Dandan Huang. 2020 · 2020
Later among the works it cites.
Oshin Agarwal, Heming Ge, Siamak Shakeri, and Rami Al-Rfou. 2021 · 2021
Closest in time.
Knowledgeable or educated guess? revisiting language models as knowledge bases
Boxi Cao, Hongyu Lin, Xianpei Han, Le Sun, Lingyong Yan, Meng Liao, Tong Xue, and Jin Xu. 2021 · 2021
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Combining pre-trained language models and structured knowledge
Pedro Colon-Hernandez, Catherine Havasi, Jason Alonso, Matthew Huggins, and Cynthia Breazeal. 2021 · 2021
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Understanding few-shot commonsense knowledge models
Jeff Da, Ronan Le Bras, Ximing Lu, Yejin Choi, and Antoine Bosselut. 2021 · 2021
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Inductive entity representations from text via link prediction
Daniel Daza, Michael Cochez, and Paul Groth. 2021 · 2021
Closest in time.
Autoregressive entity retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel, and Fabio Petroni. 2021 · 2021
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Static embeddings as efficient knowledge bases?
Philipp Dufter, Nora Kassner, and Hinrich Schütze. 2021 · 2021
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Measuring and improving consistency in pretrained language models
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard Hovy, Hinrich Schütze, and Yoav Goldberg. 2021 · 2021
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BERTese: Learning to speak to BERT
Adi Haviv, Jonathan Berant, and Amir Globerson. 2021 · 2021
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Language models as knowledge bases: On entity representations, storage capacity, and paraphrased queries
Benjamin Heinzerling and Kentaro Inui. 2021 · 2021
Closest in time.
Cskg: The commonsense knowledge graph
Filip Ilievski, Pedro Szekely, and Bin Zhang. 2021 · 2021
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"i’m not mad": Commonsense implications of negation and contradiction
Liwei Jiang, Antoine Bosselut, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
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Multilingual lama: Investigating knowledge in multilingual pretrained language models
Nora Kassner, Philipp Dufter, and Hinrich Schütze. 2021 · 2021
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Question and answer test-train overlap in open-domain question answering datasets
Patrick Lewis, Pontus Stenetorp, and Sebastian Riedel. 2021 · 2021
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Knowledge-driven data construction for zero-shot evaluation in commonsense question answering
Kaixin Ma, Filip Ilievski, Jonathan Francis, Yonatan Bisk, Eric Nyberg, and Alessandro Oltramari. 2021 · 2021
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True few-shot learning with language models
Ethan Perez, Douwe Kiela, and Kyunghyun Cho. 2021 · 2021
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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, Vladimir Karpukhin, Jean Maillard, Vassilis Plachouras, Tim Rocktäschel, and Sebastian Riedel. 2021 · 2021
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Learning how to ask: Querying LMs with mixtures of soft prompts
Guanghui Qin and Jason Eisner. 2021 · 2021
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ERICA: Improving entity and relation understanding for pre-trained language models via contrastive learning
Yujia Qin, Yankai Lin, Ryuichi Takanobu, Zhiyuan Liu, Peng Li, Heng Ji, Minlie Huang, Maosong Sun, and Jie Zhou. 2021 · 2021
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Database reasoning over text
James Thorne, Majid Yazdani, Marzieh Saeidi, Fabrizio Silvestri, Sebastian Riedel, and Alon Halevy. 2021 · 2021
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Structure-augmented text representation learning for efficient knowledge graph completion
Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Ying Wang, and Yi Chang. 2021a · 2021
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K-adapter: Infusing knowledge into pre-trained models with adapters
Ruize Wang, Duyu Tang, Nan Duan, Zhongyu Wei, Xuanjing Huang, Jianshu Ji, Guihong Cao, Daxin Jiang, and Ming Zhou. 2021c · 2021
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Machine knowledge: Creation and curation of comprehensive knowledge bases
Gerhard Weikum, Xin Luna Dong, Simon Razniewski, and Fabian M. Suchanek. 2021 · 2021
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Factual probing is [MASK]: Learning vs. learning to recall
Zexuan Zhong, Dan Friedman, and Danqi Chen. 2021 · 2021
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