Arima
Task-oriented Time Series Imputation Evaluation via Generalized Representers Zhixian Wang 1,2, Linxiao Y ang
Specifically, we summarize our contributions into the following points.
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Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking Xi Chen
To bridge this gap, we present Job-SDF, a dataset designed to train and benchmark job-skill demand forecasting models.
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AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
By introducing LLM-embedded textual timestamps, Auto-Times can utilize chronological information to align multivariate time series. Empirically, AutoTimes achieves state-of-the-art with 0.1% trainable parameters and
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