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cs.AI2026
TimeVista: Exploring and Exploiting Vision-Language Models as Judges for Time Series Forecasting
Zhi Chen, Yuxuan Wang, Jialong Wu +5
High-quality time series forecasting is pivotal for real-world decision-making. However, traditional point-wise metrics often fail to reveal complex temporal patterns and align poo…
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
Retrieval-Augmented Generation with Covariate Time Series
Kenny Ye Liang, Zhongyi Pei, Huan Zhang +3
While RAG has greatly enhanced LLMs, extending this paradigm to Time-Series Foundation Models (TSFMs) remains a challenge. This is exemplified in the Predictive Maintenance of the…