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Learning transferable representation of knowledge graphs (KGs) is challenging due to the heterogeneous, multi-relational nature of graph structures.
Kg-bert: Bert for knowledge graph completion
Liang Yao, Chengsheng Mao, and Yuan Luo. 2019 · 1909
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Wordnet: a lexical database for english
George A Miller. 1995 · 1995
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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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Relational knowledge: The foundation of higher cognition
Graeme S Halford, William H Wilson, and Steven Phillips. 2010 · 2010
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
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Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
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Knowledge graph and text jointly embedding
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014 · 2014
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Observed versus latent features for knowledge base and text inference
Kristina Toutanova and Danqi Chen. 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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Deep bidirectional language-knowledge graph pretraining
Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D Manning, Percy Liang, and Jure Leskovec. 2022 · 2015
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016 · 2016
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Representation learning of knowledge graphs with entity descriptions
Ruobing Xie, Zhiyuan Liu, Jia Jia, Huanbo Luan, and Maosong Sun. 2016 · 2016
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Analysis of the impact of negative sampling on link prediction in knowledge graphs
Bhushan Kotnis and Vivi Nastase. 2017 · 2017
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Knowledge graph embedding: A survey of approaches and applications
Quan Wang, Zhendong Mao, Bin Wang, and Li Guo. 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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Simple embedding for link prediction in knowledge graphs
Seyed Mehran Kazemi and David Poole. 2018 · 2018
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Open domain question answering using early fusion of knowledge bases and text
Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, and William Cohen. 2018a · 2018
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Multilingual knowledge graph completion via ensemble knowledge transfer
Xuelu Chen, Muhao Chen, Changjun Fan, Ankith Uppunda, Yizhou Sun, and Carlo Zaniolo. 2020 · 2020
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You can teach an old dog new tricks! on training knowledge graph embeddings
Daniel Ruffinelli, Samuel Broscheit, and Rainer Gemulla. 2020 · 2020
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Inductive relation prediction by subgraph reasoning
Komal K Teru, Etienne Denis, and William L Hamilton. 2020 · 2020
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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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HittER: Hierarchical transformers for knowledge graph embeddings
Sanxing Chen, Xiaodong Liu, Jianfeng Gao, Jian Jiao, Ruofei Zhang, and Yangfeng Ji. 2021 · 2021
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Ivana Balazevic, Carl Allen, and Timothy Hospedales. 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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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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Pytorch-biggraph: A large scale graph embedding system
Adam Lerer, Ledell Wu, Jiajun Shen, Timothee Lacroix, Luca Wehrstedt, Abhijit Bose, and Alex Peysakhovich. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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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, et al. 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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MLMLM: Link prediction with mean likelihood masked language model
Louis Clouatre, Philippe Trempe, Amal Zouaq, and Sarath Chandar. 2021 · 2021
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Inductive entity representations from text via link prediction
Daniel Daza, Michael Cochez, and Paul Groth. 2021 · 2021
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A survey on knowledge graphs: Representation, acquisition, and applications
Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, and S Yu Philip. 2021 · 2021
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Knowledge base completion meets transfer learning
Vid Kocijan and Thomas Lukasiewicz. 2021 · 2021
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KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu, Zhengyan Zhang, Zhiyuan Liu, Juanzi Li, and Jian Tang. 2021 · 2021
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StATIK: Structure and text for inductive knowledge graph completion
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Murali Annavaram, Aram Galstyan, and Greg Ver Steeg. 2022 · 2022
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Sequence-to-sequence knowledge graph completion and question answering
Apoorv Saxena, Adrian Kochsiek, and Rainer Gemulla. 2022 · 2022
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