Fetching the paper…
Reading the bibliography…
In a hyper-relational knowledge graph (HKG), each fact is composed of a main triple associated with attribute-value qualifiers, which express additional factual knowledge.
Freebase: a Collaboratively Created Graph Database for Structuring Human Knowledge. In SIGMOD . ACM, Vancouver, BC, Canada, 1247–1250
Kurt D. Bollacker, Colin Evans, Praveen K. Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
Earlier work this paper cites.
Translating Embeddings for Modeling Multi-relational Data. In NeurIPS . Curran Associates, Lake Tahoe, Nevada, United States, 2787–2795
Antoine Bordes, Nicolas Usunier, Alberto García-Durán, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Earlier work this paper cites.
Wikidata: a Free Collaborative Knowledge Base
Denny Vrandecic and Markus Krötzsch. 2014 · 2014
Earlier work this paper cites.
Knowledge Graph Embedding by Translating on Hyperplanes. In AAAI . AAAI Press, Quebec, Canada, 1112–1119
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014 · 2014
Earlier work this paper cites.
On the Representation and Embedding of Knowledge Bases beyond Binary Relations. In IJCAI . ijcai.org, New York, NY, USA, 1300–1307
Jianfeng Wen, Jianxin Li, Yongyi Mao, Shini Chen, and Richong Zhang. 2016 · 2016
Earlier work this paper cites.
Knowledge Graph Completion via Complex Tensor Factorization
Théo Trouillon, Christopher R. Dance, Éric Gaussier, Johannes Welbl, Sebastian Riedel, and Guillaume Bouchard. 2017 · 2017
Earlier work this paper cites.
Attention is All you Need. In NeurIPS . Curran Associates, Long Beach, CA, USA, 5998–6008
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. In ICLR . OpenReview.net, Vancouver, Canada, 1–15
Jie Chen, Tengfei Ma, and Cao Xiao. 2018 · 2018
Earlier work this paper cites.
Scalable Instance Reconstruction in Knowledge Bases via Relatedness Affiliated Embedding. In WWW . ACM, Lyon, France, 1185–1194
Richong Zhang, Junpeng Li, Jiajie Mei, and Yongyi Mao. 2018 · 2018
Earlier work this paper cites.
TuckER: Tensor Factorization for Knowledge Graph Completion. In EMNLP . ACL, Hong Kong, China, 5184–5193
Ivana Balazevic, Carl Allen, and Timothy M. Hospedales. 2019 · 2019
Earlier work this paper cites.
Link Prediction on N-ary Relational Data. In WWW . ACM, San Francisco, CA, USA, 583–593
Saiping Guan, Xiaolong Jin, Yuanzhuo Wang, and Xueqi Cheng. 2019 · 2019
Earlier work this paper cites.
Decoupled Weight Decay Regularization. In ICLR . OpenReview.net, New Orleans, LA, USA, 1–11
Ilya Loshchilov and Frank Hutter. 2019 · 2019
Earlier work this paper cites.
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization.. In NAACL . NAACL-HLT, Minneapolis, the United States, 2180–2189
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, and Dinh Q. Phung. 2019 · 2019
Earlier work this paper cites.
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space. In ICLR . OpenReview.net, New Orleans, LA, USA, 1–18
Zhiqing Sun, ZhiHong Deng, JianYun Nie, and Jian Tang. 2019 · 2019
Earlier work this paper cites.
Simplifying Graph Convolutional Networks. In ICML . PMLR, Long Beach, California, USA, 6861–6871
Felix Wu, Amauri H. Souza Jr., Tianyi Zhang, Christopher Fifty, Tao Yu, and Kilian Q. Weinberger. 2019 · 2019
Earlier work this paper cites.
Low-Dimensional Hyperbolic Knowledge Graph Embeddings. In ACL . ACL, Online, 6901–6914
Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, and Christopher Ré. 2020 · 2020
Earlier work this paper cites.
Knowledge Hypergraphs: Prediction Beyond Binary Relations. In IJCAI . ijcai.org, online, 2191–2197
Bahare Fatemi, Perouz Taslakian, David Vázquez, and David Poole. 2020 · 2020
Cited alongside, same era.
Message Passing for Hyper-Relational Knowledge Graphs. In EMNLP . ACL, online, 7346–7359
Mikhail Galkin, Priyansh Trivedi, Gaurav Maheshwari, Ricardo Usbeck, and Jens Lehmann. 2020 · 2020
Cited alongside, same era.
NeuInfer: Knowledge Inference on N-ary Facts. In ACL . ACL, online, 6141–6151
Saiping Guan, Xiaolong Jin, Jiafeng Guo, Yuanzhuo Wang, and Xueqi Cheng. 2020 · 2020
Cited alongside, same era.
Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases. In WWW . ACM, Taipei, China, 1104–1114
Yu Liu, Quanming Yao, and Yong Li. 2020 · 2020
Cited alongside, same era.
Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs. In NeurIPS . Online
Hongyu Ren and Jure Leskovec. 2020 · 2020
Cited alongside, same era.
Transformer-based Entity Typing in Knowledge Graphs. In EMNLP . ACL, Abu Dhabi, United Arab Emirates, 5988–6001
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li, and Jeff Z. Pan. 2022 · 2022
Later among the works it cites.
Learning Representations for Hyper-Relational Knowledge Graphs
Harry Shomer, Wei Jin, Juan-Hui Li, Yao Ma, and Jiliang Tang. 2022 · 2022
Later among the works it cites.
PolygonE: Modeling N-ary Relational Data as Gyro-Polygons in Hyperbolic Space. In AAAI . AAAI Press, online, 4308–4317
Shiyao Yan, Zequn Zhang, Xian Sun, Guangluan Xu, Shuchao Li, Qing Liu, Nayu Liu, and Shensi Wang. 2022 · 2022
Later among the works it cites.
Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers. In KDD . ACM, Long Beach, CA, USA, 310–322
Chanyoung Chung, Jaejun Lee, and Joyce Jiyoung Whang. 2023 · 2023
Later among the works it cites.
Message Function Search for Knowledge Graph Embedding. In WWW . ACM, Austin, TX, USA, 2633–2644
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction. In WWW . ACM, Taipei, China, 1885–1896
Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. 2020 · 2020
Cited alongside, same era.
Composition-based Multi-Relational Graph Convolutional Networks. In ICLR . OpenReview.net, Addis Ababa, Ethiopia, 1–15
Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, and Partha P. Talukdar. 2020 · 2020
Cited alongside, same era.
L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks. In CVPR . IEEE, Seattle, WA, USA, 2124–2132
Yuning You, Tianlong Chen, Zhangyang Wang, and Yang Shen. 2020 · 2020
Cited alongside, same era.
Searching to Sparsify Tensor Decomposition for N-ary Relational Data. In WWW . ACM, online, 4043–4054
Shimin Di, Quanming Yao, and Lei Chen. 2021 · 2021
Cited alongside, same era.
Role-Aware Modeling for N-ary Relational Knowledge Bases. In WWW . ACM, Ljubljana, Slovenia, 2660–2671
Yu Liu, Quanming Yao, and Yong Li. 2021 · 2021
Cited alongside, same era.
Context-aware Entity Typing in Knowledge Graphs. In EMNLP . ACL, online, 2240–2250
Weiran Pan, Wei Wei, and Xian-Ling Mao. 2021 · 2021
Cited alongside, same era.
Link Prediction on N-ary Relational Facts: A Graph-based Approach. In ACL . ACL, online, 396–407
Quan Wang, Haifeng Wang, Yajuan Lyu, and Yong Zhu. 2021 · 2021
Cited alongside, same era.
Shimin Di and Lei Chen. 2023 · 2023
Later among the works it cites.
Link Prediction on N-ary Relational Data Based on Relatedness Evaluation
Saiping Guan, Xiaolong Jin, Jiafeng Guo, Yuanzhuo Wang, and Xueqi Cheng. 2023 · 2023
Later among the works it cites.
HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion. In CIKM . ACM, Birmingham, UK, 803–812
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li, and Jeff Z. Pan. 2023 · 2023
Later among the works it cites.
Schema-Aware Hyper-Relational Knowledge Graph Embeddings for Link Prediction
Yuhuan Lu, Dingqi Yang, Pengyang Wang, Paolo Rosso, and Philippe Cudre-Mauroux. 2023b · 2023
Later among the works it cites.
HAHE: Hierarchical Attention for Hyper-Relational Knowledge Graphs in Global and Local Level. In ACL . ACL, Toronto, Canada, 8095–8107
Haoran Luo, Haihong E, Yuhao Yang, Yikai Guo, Mingzhi Sun, Tianyu Yao, Zichen Tang, Kaiyang Wan, Meina Song, and Wei Lin. 2023 · 2023
Later among the works it cites.
HyConvE: A Novel Embedding Model for Knowledge Hypergraph Link Prediction with Convolutional Neural Networks. In WWW . ACM, Austin, TX, USA, 188–198
Chenxu Wang, Xin Wang, Zhao Li, Zirui Chen, and Jianxin Li. 2023 · 2023
Later among the works it cites.
Shrinking Embeddings for Hyper-Relational Knowledge Graphs. In ACL . ACL, Toronto, Canada, 13306–13320
Bo Xiong, Mojtaba Nayyeri, Shirui Pan, and Steffen Staab. 2023 · 2023
Later among the works it cites.
HJE: Joint Convolutional Representation Learning for Knowledge Hypergraph Completion
Zhao Li, Chenxu Wang, Xin Wang, Zirui Chen, and Jianxin Li. 2024b · 2024
Closest in time.
HyCubE: Efficient Knowledge Hypergraph 3D Circular Convolutional Embedding
Zhao Li, Xin Wang, Jianxin Li, Wenbin Guo, and Jun Zhao. 2024a · 2024
Closest in time.
HyperCL: A Contrastive Learning Framework for Hyper-Relational Knowledge Graph Embedding with Hierarchical Ontology. In ACL . ACL, Bangkok, Thailand, 2918–2929
Yuhuan Lu, Weijian Yu, Xin Jing, and Dingqi Yang. 2024 · 2024
Closest in time.
Robust Link Prediction over Noisy Hyper-Relational Knowledge Graphs via Active Learning. In WWW . ACM, Singapore, 2282–2293
Weijian Yu, Jie Yang, and Dingqi Yang. 2024 · 2024
Closest in time.