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Knowledge graph completion aims to address the problem of extending a KG with missing triples.
Translating embeddings for modeling multi-relational data. In Proc. of NeurIPS
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Earlier work this paper cites.
Representing Text for Joint Embedding of Text and Knowledge Bases. In Proc. of EMNLP
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon. 2015 · 2015
Earlier work this paper cites.
Embedding Entities and Relations for Learning and Inference in Knowledge Bases. In Proc. of ICLR
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2015 · 2015
Earlier work this paper cites.
Complex Embeddings for Simple Link Prediction. In Proc. of ICML
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016 · 2016
Earlier work this paper cites.
Convolutional 2D Knowledge Graph Embeddings. In Proc. of AAAI
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Earlier work this paper cites.
TuckER: Tensor Factorization for Knowledge Graph Completion. In Proc. of EMNLP
Ivana Balazevic, Carl Allen, and Timothy M. Hospedales. 2019 · 2019
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proc. of NAACL
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs. In Proc. of ACL
Deepak Nathani, Jatin Chauhan, Charu Sharma, and Manohar Kaul. 2019 · 2019
Cited alongside, same era.
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space. In ICLR
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, and Jian Tang. 2019 · 2019
Cited alongside, same era.
KG-BERT: BERT for Knowledge Graph Completion
Liang Yao, Chengsheng Mao, and Yuan Luo. 2019 · 2019
Cited alongside, same era.
Low-Dimensional Hyperbolic Knowledge Graph Embeddings. In Proc. of ACL
Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, and Christopher Ré. 2020 · 2020
Cited alongside, same era.
Autoregressive Entity Retrieval. In Proc. of ICLR
Nicola De Cao, Gautier Izacard, Sebastian Riedel, and Fabio Petroni. 2021 · 2021
Later among the works it cites.
GenIE: Generative Information Extraction
Martin Josifoski, Nicola De Cao, Maxime Peyrard, and Robert West. 2021 · 2021
Later among the works it cites.
Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion. In Proc. of WWW
Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Ying Wang, and Yi Chang. 2021 · 2021
Later among the works it cites.
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs
Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, and Feng Wu. 2021 · 2021
Later among the works it cites.
Ontology-enhanced Prompt-tuning for Few-shot Learning. In Proc. of WWW
Hongbin Ye, Ningyu Zhang, Shumin Deng, Xiang Chen, Hui Chen, Feiyu Xiong, Xi Chen, and Huajun Chen. 2022 · 2022
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Reasoning Through Memorization: Nearest Neighbor Knowledge Graph Embeddings
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Relation Adversarial Network for Low resource Knowledge Graph Completion. In Proc. of WWW
Ningyu Zhang, Shumin Deng, Zhanlin Sun, Jiaoyan Chen, Wei Zhang, and Huajun Chen. 2020 · 2020
Cited alongside, same era.
OntoProtein: Protein Pretraining With Gene Ontology Embedding. In Proc. of ICLR
Ningyu Zhang, Zhen Bi, Xiaozhuan Liang, Siyuan Cheng, Haosen Hong, Shumin Deng, Jiazhang Lian, Qiang Zhang, and Huajun Chen. 2022a
Cited in the paper.
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. In Proc. of ICLR
Ningyu Zhang, Luoqiu Li, Xiang Chen, Shumin Deng, Zhen Bi, Chuanqi Tan, Fei Huang, and Huajun Chen. 2022b
Cited in the paper.
Ningyu Zhang, Xin Xie, Xiang Chen, Shumin Deng, Chuanqi Tan, Fei Huang, Xu Cheng, and Huajun Chen. 2022c · 2022
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