6 citations · 12 across the 3 of their papers we have counts for
8 papers
Deep Structural Point Process for Learning Temporal Interaction Networks
Jiangxia Cao, Xixun Lin, Xin Cong +4
This work investigates the problem of learning temporal interaction networks. A temporal interaction network consists of a series of chronological interactions between users and it…
Task-adaptive Neural Process for User Cold-Start Recommendation
Xixun Lin, Jia Wu, Chuan Zhou +3
User cold-start recommendation is a long-standing challenge for recommender systems due to the fact that only a few interactions of cold-start users can be exploited. Recent studie…
Bipartite Graph Embedding via Mutual Information Maximization
Jiangxia Cao, Xixun Lin, Shu Guo +3
Bipartite graph embedding has recently attracted much attention due to the fact that bipartite graphs are widely used in various application domains. Most previous methods, which a…
Few-Shot Event Detection with Prototypical Amortized Conditional Random Field
Xin Cong, Shiyao Cui, Bowen Yu +3
Event detection tends to struggle when it needs to recognize novel event types with a few samples. The previous work attempts to solve this problem in the identify-then-classify ma…
Graph Geometry Interaction Learning
Shichao Zhu, Shirui Pan, Chuan Zhou +3
While numerous approaches have been developed to embed graphs into either Euclidean or hyperbolic spaces, they do not fully utilize the information available in graphs, or lack the…
Coarse-to-Fine Pre-training for Named Entity Recognition
Mengge Xue, Bowen Yu, Zhenyu Zhang +3
More recently, Named Entity Recognition hasachieved great advances aided by pre-trainingapproaches such as BERT. However, currentpre-training techniques focus on building lan-guage…