274 citations · 579 across the 35 of their papers we have counts for
5 papers · 1 filter
Principled Representation Learning for Entity Alignment
Lingbing Guo, Zequn Sun, Mingyang Chen +3
Embedding-based entity alignment (EEA) has recently received great attention. Despite significant performance improvement, few efforts have been paid to facilitate understanding of…
Knowing False Negatives: An Adversarial Training Method for Distantly Supervised Relation Extraction
Kailong Hao, Botao Yu, Wei Hu
Distantly supervised relation extraction (RE) automatically aligns unstructured text with relation instances in a knowledge base (KB). Due to the incompleteness of current KBs, sen…
A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
Nikunj Saunshi, Arushi Gupta, Wei Hu
An effective approach in meta-learning is to utilize multiple "train tasks" to learn a good initialization for model parameters that can help solve unseen "test tasks" with very fe…
Knowing the No-match: Entity Alignment with Dangling Cases
Zequn Sun, Muhao Chen, Wei Hu
This paper studies a new problem setting of entity alignment for knowledge graphs (KGs). Since KGs possess different sets of entities, there could be entities that cannot find alig…
Learning Fine-grained Fact-Article Correspondence in Legal Cases
Jidong Ge, Yunyun huang, Xiaoyu Shen +2
Automatically recommending relevant law articles to a given legal case has attracted much attention as it can greatly release human labor from searching over the large database of…