10 citations · 17 across the 10 of their papers we have counts for
10 papers
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…
How to Unlock Time Series Editing? Diffusion-Driven Approach with Multi-Grained Control
Hao Yu, Chu Xin Cheng, Runlong Yu +4
Recent advances in time series generation have shown promise, yet controlling properties in generated sequences remains challenging. Time Series Editing (TSE) - making precise modi…
Multi-granularity Interest Retrieval and Refinement Network for Long-Term User Behavior Modeling in CTR Prediction
Xiang Xu, Hao Wang, Wei Guo +6
Click-through Rate (CTR) prediction is crucial for online personalization platforms. Recent advancements have shown that modeling rich user behaviors can significantly improve the…
Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation
Yuyang Ye, Zhi Zheng, Yishan Shen +6
Recent advances in Large Language Models (LLMs) have demonstrated significant potential in the field of Recommendation Systems (RSs). Most existing studies have focused on converti…
PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization
Yuyang Ye, Lu-An Tang, Haoyu Wang +5
Achieving carbon neutrality within industrial operations has become increasingly imperative for sustainable development. It is both a significant challenge and a key opportunity fo…
Cognitive Evolutionary Learning to Select Feature Interactions for Recommender Systems
Runlong Yu, Qixiang Shao, Qi Liu +2
Feature interaction selection is a fundamental problem in commercial recommender systems. Most approaches equally enumerate all features and interactions by the same pre-defined op…