5 papers
An Adversarial Transfer Network for Knowledge Representation Learning
Huijuan Wang, Shuangyin Li, Rong Pan
Knowledge representation learning has received a lot of attention in the past few years. The success of existing methods heavily relies on the quality of knowledge graphs. The enti…
Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding
Peifeng Wang, Jialong Han, Chenliang Li +1
Knowledge graph embedding aims at modeling entities and relations with low-dimensional vectors. Most previous methods require that all entities should be seen during training, whic…
Incorporating GAN for Negative Sampling in Knowledge Representation Learning
Peifeng Wang, Shuangyin Li, Rong pan
Knowledge representation learning aims at modeling knowledge graph by encoding entities and relations into a low dimensional space. Most of the traditional works for knowledge embe…
Operations Guided Neural Networks for High Fidelity Data-To-Text Generation
Feng Nie, Jinpeng Wang, Jin-Ge Yao +2
Recent neural models for data-to-text generation are mostly based on data-driven end-to-end training over encoder-decoder networks. Even though the generated texts are mostly fluen…
Incorporating Consistency Verification into Neural Data-to-Document Generation
Feng Nie, Hailin Chen, Jinpeng Wang +3
Recent neural models for data-to-document generation have achieved remarkable progress in producing fluent and informative texts. However, large proportions of generated texts do n…