collaborators

9 papers

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.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.LG2026

Deep Time Series Models: A Comprehensive Survey and Benchmark

Yuxuan Wang, Haixu Wu, Jiaxiang Dong +4

Time series, characterized by a sequence of data points organized in a discrete-time order, are ubiquitous in real-world scenarios. Unlike other data modalities, time series presen…

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.LG2026

Aura: Universal Multi-dimensional Exogenous Integration for Aviation Time Series

Jiafeng Lin, Mengren Zheng, Simeng Ye +5

Time series forecasting has witnessed an increasing demand across diverse industrial applications, where accurate predictions are pivotal for informed decision-making. Beyond numer…

cs.CL2026

Thoth: Mid-Training Bridges LLMs to Time Series Understanding

Jiafeng Lin, Yuxuan Wang, Jialong Wu +3

Large Language Models (LLMs) have demonstrated remarkable success in general-purpose reasoning. However, they still struggle to understand and reason about time series data, which…