2.2k citations · 2.3k across the 10 of their papers we have counts for
10 papers
Knowledge Graph Embedding by Normalizing Flows
Changyi Xiao, Xiangnan He, Yixin Cao
A key to knowledge graph embedding (KGE) is to choose a proper representation space, e.g., point-wise Euclidean space and complex vector space. In this paper, we propose a unified…
Training Free Graph Neural Networks for Graph Matching
Zhiyuan Liu, Yixin Cao, Fuli Feng +4
We present a framework of Training Free Graph Matching (TFGM) to boost the performance of Graph Neural Networks (GNNs) based graph matching, providing a fast promising solution wit…
Are Missing Links Predictable? An Inferential Benchmark for Knowledge Graph Completion
Yixin Cao, Xiang Ji, Xin Lv +3
We present InferWiki, a Knowledge Graph Completion (KGC) dataset that improves upon existing benchmarks in inferential ability, assumptions, and patterns. First, each testing sampl…
How Knowledge Graph and Attention Help? A Quantitative Analysis into Bag-level Relation Extraction
Zikun Hu, Yixin Cao, Lifu Huang +1
Knowledge Graph (KG) and attention mechanism have been demonstrated effective in introducing and selecting useful information for weakly supervised methods. However, only qualitati…
Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition
Meihan Tong, Shuai Wang, Bin Xu +4
Few-shot Named Entity Recognition (NER) exploits only a handful of annotations to identify and classify named entity mentions. Prototypical network shows superior performance on fe…
Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen
Yixin Cao, Ruihao Shui, Liangming Pan +3
The curse of knowledge can impede communication between experts and laymen. We propose a new task of expertise style transfer and contribute a manually annotated dataset with the g…
Reinforced Negative Sampling over Knowledge Graph for Recommendation
Xiang Wang, Yaokun Xu, Xiangnan He +3
Properly handling missing data is a fundamental challenge in recommendation. Most present works perform negative sampling from unobserved data to supply the training of recommender…
KGAT: Knowledge Graph Attention Network for Recommendation
Xiang Wang, Xiangnan He, Yixin Cao +2
To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account. Traditional…
A note on small cuts for a terminal
Yixin Cao
Given a graph and a terminal , a cut for is a vertex set that contains . We look for a cut that is small in two senses, i.e., there are no more than…
FAST: Kernelization based on Graph Modular Decomposition
Yixin Cao, Jianer Chen
Kernelization algorithms, usually a preprocessing step before other more traditional algorithms, are very special in the sense that they return (reduced) instances, instead of fina…