12 citations · 40 across the 20 of their papers we have counts for
7 papers · 1 filter
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach
Hanyang Yuan, Jiarong Xu, Renhong Huang +3
Graph neural networks (GNNs) have attracted considerable attention due to their diverse applications. However, the scarcity and quality limitations of graph data present challenges…
Ca2-VDM: Efficient Autoregressive Video Diffusion Model with Causal Generation and Cache Sharing
Kaifeng Gao, Jiaxin Shi, Hanwang Zhang +3
With the advance of diffusion models, today's video generation has achieved impressive quality. To extend the generation length and facilitate real-world applications, a majority o…
ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models
Kaifeng Gao, Jiaxin Shi, Hanwang Zhang +2
With the advance of diffusion models, today's video generation has achieved impressive quality. But generating temporal consistent long videos is still challenging. A majority of v…
: Discrete Diffusion Model for Occluded 3D Human Pose Estimation
Weiquan Wang, Jun Xiao, Chunping Wang +3
Continuous diffusion models have demonstrated their effectiveness in addressing the inherent uncertainty and indeterminacy in monocular 3D human pose estimation (HPE). Despite thei…
Seeing Beyond Classes: Zero-Shot Grounded Situation Recognition via Language Explainer
Jiaming Lei, Lin Li, Chunping Wang +2
Benefiting from strong generalization ability, pre-trained vision language models (VLMs), e.g., CLIP, have been widely utilized in zero-shot scene understanding. Unlike simple reco…
Graph-Skeleton: ~1% Nodes are Sufficient to Represent Billion-Scale Graph
Linfeng Cao, Haoran Deng, Yang Yang +2
Due to the ubiquity of graph data on the web, web graph mining has become a hot research spot. Nonetheless, the prevalence of large-scale web graphs in real applications poses sign…
Enhancing Cross-domain Link Prediction via Evolution Process Modeling
Xuanwen Huang, Wei Chow, Yize Zhu +5
This work proposes DyExpert, a dynamic graph model for cross-domain link prediction. It can explicitly model historical evolving processes to learn the evolution pattern of a speci…