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Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links.
Kg-bert: Bert for knowledge graph completion
Liang Yao, Chengsheng Mao, and Yuan Luo. 2019 · 1909
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam M. Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, W. Li, and Peter J. Liu. 2019 · 1910
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WordNet: A lexical database for English
George A. Miller. 1992 · 1992
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Yago: a core of semantic knowledge
Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2007 · 2007
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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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Visualizing data using t-sne
L. V. D. Maaten and Geoffrey E. Hinton. 2008 · 2008
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Boosting contrastive self-supervised learning with false negative cancellation
Tri Huynh, Simon Kornblith, Matthew R. Walter, Michael Maire, and Maryam Khademi. 2020 · 2011
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A three-way model for collective learning on multi-relational data
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Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
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Knowledge graph embedding by translating on hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014 · 2014
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Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon. 2015 · 2015
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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2015 · 2015
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Representation learning of knowledge graphs with entity descriptions
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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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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
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Improving sequential recommendation with knowledge-enhanced memory networks
Jin Huang, Wayne Xin Zhao, Hongjian Dou, Ji-Rong Wen, and Edward Y. Chang. 2018 · 2018
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Improving language understanding by generative pre-training
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TuckER: Tensor factorization for knowledge graph completion
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Nils Reimers and Iryna Gurevych. 2019 · 2019
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Haitian Sun, Tania Bedrax-Weiss, and William Cohen. 2019a · 2019
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Rotate: Knowledge graph embedding by relational rotation in complex space
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Inductive relation prediction by subgraph reasoning
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Large batch optimization for deep learning: Training BERT in 76 minutes
Yang You, Jing Li, Sashank J. Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, and Cho-Jui Hsieh. 2020 · 2020
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Are missing links predictable? an inferential benchmark for knowledge graph completion
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Inductive entity representations from text via link prediction
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Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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Learning transferable visual models from natural language supervision
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Structure-augmented text representation learning for efficient knowledge graph completion
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Understanding the behaviour of contrastive loss
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
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Inductive relation prediction by bert
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Factual probing is [MASK]: Learning vs. learning to recall
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016 · 2080
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