79 citations · 588 across the 46 of their papers we have counts for
7 papers · 1 filter
Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction
Xuming Hu, Shiao Meng, Chenwei Zhang +4
Information Extraction (IE) aims to extract structured information from heterogeneous sources. IE from natural language texts include sub-tasks such as Named Entity Recognition (NE…
Hyperbolic Graph Representation Learning: A Tutorial
Min Zhou, Menglin Yang, Lujia Pan +1
Graph-structured data are widespread in real-world applications, such as social networks, recommender systems, knowledge graphs, chemical molecules etc. Despite the success of Eucl…
Knowledge-aware Neural Networks with Personalized Feature Referencing for Cold-start Recommendation
Xinni Zhang, Yankai Chen, Cuiyun Gao +3
Incorporating knowledge graphs (KGs) as side information in recommendation has recently attracted considerable attention. Despite the success in general recommendation scenarios, p…
HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization
Menglin Yang, Min Zhou, Jiahong Liu +2
In large-scale recommender systems, the user-item networks are generally scale-free or expand exponentially. The latent features (also known as embeddings) used to describe the use…
Text Revision by On-the-Fly Representation Optimization
Jingjing Li, Zichao Li, Tao Ge +2
Text revision refers to a family of natural language generation tasks, where the source and target sequences share moderate resemblance in surface form but differentiate in attribu…
CenGCN: Centralized Convolutional Networks with Vertex Imbalance for Scale-Free Graphs
Feng Xia, Lei Wang, Tao Tang +4
Graph Convolutional Networks (GCNs) have achieved impressive performance in a wide variety of areas, attracting considerable attention. The core step of GCNs is the information-pas…