6 citations · 18 across the 16 of their papers we have counts for
3 papers · 1 filter
Augur: Modeling Covariate Causal Associations in Time Series via Large Language Models
Zhiqing Cui, Binwu Wang, Qingxiang Liu +4
Large language models (LLM) have emerged as a promising avenue for time series forecasting, offering the potential to integrate multimodal data. However, existing LLM-based approac…
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
Sisuo Lyu, Siru Zhong, Weilin Ruan +4
Time series forecasting is fundamental to diverse applications, with recent approaches leverage large vision models (LVMs) to capture temporal patterns through visual representatio…
GDformer: Going Beyond Subsequence Isolation for Multivariate Time Series Anomaly Detection
Qingxiang Liu, Xiaoliang Luo, Chenghao Liu +5
Unsupervised anomaly detection of multivariate time series is a challenging task, given the requirements of deriving a compact detection criterion without accessing the anomaly poi…