5 papers · 1 filter
Estimating Time Series Foundation Model Transferability via In-Context Learning
Qingren Yao, Ming Jin, Chengqi Zhang +3
Time series foundation models (TSFMs) offer strong zero-shot forecasting via large-scale pre-training, yet fine-tuning remains critical for boosting performance in domains with lim…
TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models
Tong Guan, Zijie Meng, Dianqi Li +7
Recent advances in multimodal time series learning underscore a paradigm shift from analytics centered on basic patterns toward advanced time series understanding and reasoning. Ho…
LeForecast: Enterprise Hybrid Forecast by Time Series Intelligence
Zheng Tan, Yiwen Nie, Wenfa Wu +22
Demand is spiking in industrial fields for multidisciplinary forecasting, where a broad spectrum of sectors needs planning and forecasts to streamline intelligent business manageme…
Towards Neural Scaling Laws for Time Series Foundation Models
Qingren Yao, Chao-Han Huck Yang, Renhe Jiang +3
Scaling laws offer valuable insights into the design of time series foundation models (TSFMs). However, previous research has largely focused on the scaling laws of TSFMs for in-di…
DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection
Chaocheng Yang, Tingyin Wang, Xuanhui Yan
Anomaly detection in multivariate time series has emerged as a crucial challenge in time series research, with significant research implications in various fields such as fraud det…