9 citations · 14 across the 6 of their papers we have counts for
6 papers
Spiking Variational Graph Auto-Encoders for Efficient Graph Representation Learning
Hanxuan Yang, Ruike Zhang, Qingchao Kong +1
Graph representation learning is a fundamental research issue and benefits a wide range of applications on graph-structured data. Conventional artificial neural network-based metho…
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval
Zhixiong Zeng, Wenji Mao
Cross-Modal Retrieval (CMR) is an important research topic across multimodal computing and information retrieval, which takes one type of data as the query to retrieve relevant dat…
AnANet: Modeling Association and Alignment for Cross-modal Correlation Classification
Nan Xu, Junyan Wang, Yuan Tian +2
The explosive increase of multimodal data makes a great demand in many cross-modal applications that follow the strict prior related assumption. Thus researchers study the definiti…
A Deep Latent Space Model for Graph Representation Learning
Hanxuan Yang, Qingchao Kong, Wenji Mao
Graph representation learning is a fundamental problem for modeling relational data and benefits a number of downstream applications. Traditional Bayesian-based graph models and re…
A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking
Shuai Wang, Penghui Wei, Qingchao Kong +1
To inhibit the spread of rumorous information and its severe consequences, traditional fact checking aims at retrieving relevant evidence to verify the veracity of a given claim. F…
Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and Veracity
Penghui Wei, Nan Xu, Wenji Mao
Automatically verifying rumorous information has become an important and challenging task in natural language processing and social media analytics. Previous studies reveal that pe…