11 papers
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…
SSDA: Bridging Spectral and Structural Gaps via Dual Adaptation for Vision-Based Time Series Forecasting
Mingrui Zhang, Hanchen Yang, Wengen Li +4
Large vision models (LVMs) have recently proven to be surprisingly effective time series forecasters, simply by rendering temporal data as images. This success, how ever, rests on…
AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting
Xudong Jiang, Mingshan Loo, Hanchen Yang +5
Accurate long-term time series forecasting (LTSF) requires the capture of complex long-range dependencies and dynamic periodic patterns. Recent advances in frequency-domain analysi…
ImmerIris: A Large-Scale Dataset and Benchmark for Off-Axis and Unconstrained Iris Recognition in Immersive Applications
Yuxi Mi, Qiuyang Yuan, Zhizhou Zhong +5
Recently, iris recognition is regaining prominence in immersive applications such as extended reality as a means of seamless user identification. This application scenario introduc…
One Pass for All: A Discrete Diffusion Model for Knowledge Graph Triple Set Prediction
Jihong Guan, Jiaqi Wang, Wengen Li +3
Knowledge Graphs (KGs) are composed of triples, and the goal of Knowledge Graph Completion (KGC) is to infer the missing factual triples. Traditional KGC tasks predict missing elem…