3 papers
cs.LG2026
Exploring Accuracy Law for Deep Time Series Forecasters: An Empirical Study
Yuxuan Wang, Haixu Wu, Yuezhou Ma +8
Deep time series forecasting has emerged as a rapidly growing field in recent years. Despite the exponential growth of community interests, progress on standard benchmarks is often…
cs.AI2026
Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling
Yong Liu, Xingjian Su, Shiyu Wang +7
We introduce Timer-S1, a strong Mixture-of-Experts (MoE) time series foundation model with 8.3B total parameters, 0.75B activated parameters for each token, and a context length of…
cs.AI2026
EventCast: Hybrid Demand Forecasting in E-Commerce with LLM-Based Event Knowledge
Congcong Hu, Yuang Shi, Fan Huang +4
Demand forecasting is a cornerstone of e-commerce operations, directly impacting inventory planning and fulfillment scheduling. However, existing forecasting systems often fail dur…