3 papers
cs.LG2025
Bridging the Last Mile of Prediction: Enhancing Time Series Forecasting with Conditional Guided Flow Matching
Huibo Xu, Runlong Yu, Likang Wu +2
Existing generative models for time series forecasting often transform simple priors (typically Gaussian) into complex data distributions. However, their sampling initialization, i…
cs.IR2025
From Entity Reliability to Clean Feedback: An Entity-Aware Denoising Framework Beyond Interaction-Level Signals
Ze Liu, Xianquan Wang, Shuochen Liu +5
Implicit feedback is central to modern recommender systems but is inherently noisy, often impairing model training and degrading user experience. At scale, such noise can mislead l…
cs.LG2025
NeuTSFlow: Modeling Continuous Functions Behind Time Series Forecasting
Huibo Xu, Likang Wu, Xianquan Wang +4
Time series forecasting is a fundamental task with broad applications, yet conventional methods often treat data as discrete sequences, overlooking their origin as noisy samples of…