30 citations · 30 across the 13 of their papers we have counts for
13 papers
Adaptive Item-based Collaborative Structures via Noise Rescheduling in Diffusion for Generative Recommendation
Jiaqi Wang, Tianying Liu, Heng Chang +3
Discrete Diffusion Models (DDMs) have recently been introduced to recommendation systems, modeling user history as a token generation process via iterative denoising. However, whil…
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…
DiffTSP: A Conditional Discrete Diffusion Model for Knowledge Graph Triple Set Prediction
Jihong Guan, Jiaqi Wang, Wengen Li +5
Triple set prediction (TSP) aims to discover missing facts from an incomplete knowledge graph without predefined queries. Existing approaches typically construct the predicted set…