3 papers
cs.LG2026
CTQWformer: A CTQW-based Transformer for Graph Classification
Zhan Li, Wuqing Yu, Yusen Wu +1
Graph Neural Networks (GNN) and Transformer-based architectures have achieved remarkable progress in graph learning, yet they still struggle to capture both global structural depen…
cs.CV2026
EagleNet: Energy-Aware Fine-Grained Relationship Learning Network for Text-Video Retrieval
Yuhan Chen, Pengwen Dai, Chuan Wang +2
Text-video retrieval tasks have seen significant improvements due to the recent development of large-scale vision-language pre-trained models. Traditional methods primarily focus o…
cs.CV2026
SDPose: Exploiting Diffusion Priors for Out-of-Domain and Robust Pose Estimation
Shuang Liang, Jing He, Chuanmeizhi Wang +4
Pre-trained diffusion models provide rich latent features across U-Net levels and are emerging as powerful vision backbones. While prior works such as Marigold and Lotus repurpose…