Separate-and-Aggregate: A Transformer-based Patch Refinement Model for
Knowledge Graph Completion

Separate-and-Aggregate: A Transformer-based Patch Refinement Model for Knowledge Graph Completion

11 July 2023

Kwok-Yan Lam

Papers citing "Separate-and-Aggregate: A Transformer-based Patch Refinement Model for Knowledge Graph Completion"

8 / 8 papers shown

Title
Threats, Attacks, and Defenses in Machine Unlearning: A Survey Ziyao Liu Huanyi Ye Chen Chen Yongsen Zheng K. Lam AAML MU 57 30 0 20 Mar 2024
Knowledge Graph Embedding with Atrous Convolution and Residual Learning Feiliang Ren Jucheng Li Huihui Zhang Shilei Liu Bochao Li Ruicheng Ming Yujia Bai 80 35 0 23 Oct 2020
KG-BERT: BERT for Knowledge Graph Completion Liang Yao Chengsheng Mao Yuan Luo SLR 37 582 0 07 Sep 2019
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks Jiasen Lu Dhruv Batra Devi Parikh Stefan Lee SSL VLM 162 3,659 0 06 Aug 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 331 24,160 0 26 Jul 2019
Modeling Relational Data with Graph Convolutional Networks Michael Schlichtkrull Thomas Kipf Peter Bloem Rianne van den Berg Ivan Titov Max Welling GNN 116 4,772 0 17 Mar 2017
Layer Normalization Jimmy Lei Ba J. Kiros Geoffrey E. Hinton 185 10,412 0 21 Jul 2016
Embedding Entities and Relations for Learning and Inference in Knowledge Bases Bishan Yang Wen-tau Yih Xiaodong He Jianfeng Gao Li Deng NAI 49 3,174 0 20 Dec 2014