79 citations · 274 across the 14 of their papers we have counts for
12 papers
Mixed Attention Network for Cross-domain Sequential Recommendation
Guanyu Lin, Chen Gao, Yu Zheng +8
In modern recommender systems, sequential recommendation leverages chronological user behaviors to make effective next-item suggestions, which suffers from data sparsity issues, es…
Improved Techniques for Training Consistency Models
Yang Song, Prafulla Dhariwal
Consistency models are a nascent family of generative models that can sample high quality data in one step without the need for adversarial training. Current consistency models ach…
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach
Kai Zhao, Qiyu Kang, Yang Song +3
Graph neural networks (GNNs) are vulnerable to adversarial perturbations, including those that affect both node features and graph topology. This paper investigates GNNs derived fr…
Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation
Yunzhu Pan, Chen Gao, Jianxin Chang +5
Sequential recommendation is one of the most important tasks in recommender systems, which aims to recommend the next interacted item with historical behaviors as input. Traditiona…
Graph Contrastive Learning with Generative Adversarial Network
Cheng Wu, Chaokun Wang, Jingcao Xu +5
Graph Neural Networks (GNNs) have demonstrated promising results on exploiting node representations for many downstream tasks through supervised end-to-end training. To deal with t…
HypLiLoc: Towards Effective LiDAR Pose Regression with Hyperbolic Fusion
Sijie Wang, Qiyu Kang, Rui She +4
LiDAR relocalization plays a crucial role in many fields, including robotics, autonomous driving, and computer vision. LiDAR-based retrieval from a database typically incurs high c…