5 papers
Ghost: Plausible Yet Unlearnable Trajectories via On-Manifold Substitution for Next-POI Privacy
Zhenyu Yu, Jihong Guan, Shuigeng Zhou
A publisher who releases check-in trajectories inadvertently publishes a strong predictor of every user's future locations. We address this risk by generating unlearnable trajector…
FlowTime: Towards Continuous Generative Watch Time Prediction via Flow-based Personalized Priors
Hongxu Ma, Han Zhou, Chenghou Jin +5
Watch time has emerged as a pivotal metric for optimizing deep user engagement in short-video recommender systems. However, current methods of watch time prediction (WTP) suffer fr…
DiffoR: A Unified Continuous Generative Framework for Universal Ordinal Regression
Hongxu Ma, Lin Wang, Chenghou Jin +6
Ordinal Regression (OR) aims to predict target values with inherent order, underpinning critical applications across diverse domains, from recommender systems to computer vision. T…
CaST-POI: Candidate-Conditioned Spatiotemporal Modeling for Next POI Recommendation
Zhenyu Yu, Chunlei Meng, Yangchen Zeng +3
Next Point-of-Interest (POI) recommendation ranks a user's likely next location based on check-in history. Most recent rankers compress the trajectory into a single user vector and…
Fine-Grained Zero-Shot Object Detection
Hongxu Ma, Chenbo Zhang, Lu Zhang +3
Zero-shot object detection (ZSD) aims to leverage semantic descriptions to localize and recognize objects of both seen and unseen classes. Existing ZSD works are mainly coarse-grai…